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Open main menu [ OMS Reviews](https://www.omscentral.com/) [Home](https://www.omscentral.com/) Reviews [OMSCS Notes](https://omscs-notes.com/) [Add Review](https://www.omscentral.com/reviews/new) Open GitHub menu ### 100 Most Recent Reviews - Bt0s2h6ErpUV5XlCbPyEcg== March 24, 2026 spring 2026 [Introduction to Analytics Modeling](https://www.omscentral.com/courses/introduction-to-analytics-modeling/reviews) Dreadful, actually pathetic that a top 5 school allows this course. The lectures too sparsely cover too many models, the homework are LLM coding exercises with no feedback beyond thumbs-up emojis or trivial formatting criticisms, and the exams are largely indecipherable. If you want a basic introduction to ML, statquest is an order of magnitude better than 6501 and 100% free. I am astounded this class is rated so high and chalk it up to people with CS undergrads or people with low standards. This course is so bad but rated so high I withdrew from the entire program. Most of the other required courses are in the low 2s. Shocking, because I can't even imagine how bad they must be after taking this one. Rating: 1 / 5Difficulty: 2 / 5Workload: 10 hours / week - J2D54Vgzw983EqL0aj+WkA== March 23, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) Lectures: Lectures from Prof Riedl are mostly good. Meta lectures are mostly terrible - presenters just reading dense slides at the camera. Lecture errata are in a separate Word document instead of just being added below the actual lectures. Also, lectures can only be viewed through Canvas instead of Ed Lessons for some reason. Quizzes: Weekly quizzes proctored with Honorlock (closed everything). Quiz weighting is 10% as of spring 2026. Sometimes the questions are worded quite poorly. Exams: 20% midterm, 20% final, closed everything and proctored with Honorlock as of spring 2026. I’ve only taken the midterm so far. The midterm exam was a mix of multiple choice single answer, multiple choice multi-answer (sometimes with MANY options), and free response. Not many questions - make a mistake on one question and your overall grade will take a substantial hit. A practice midterm was given, but much easier than the actual midterm. Instead of curving the midterm, a "midterm retake quiz" was offered so students could try to improve their scores on a few select questions that were poorly written. Homework: Assignments 1-4 are too simple and the tests are not rigorous. You can get 100% without really understanding. The professor has admitted this is the reason for reducing the weight of homework assignments in the final grade. Between 2 to 8 hours to complete each one. Most of the time is trying to understand the misleading instructions or figuring out the bugs in the code that is provided (and you aren’t supposed to modify). Course staff: TAs are mostly slow to respond if they respond at all. The head IA (initials FPG) is actively unhelpful and refuses to respond to any questions regarding course policy interpretation. Time commitment: Mostly low outside of exams. tl;dr: No longer the easy A that it was in previous semesters. Take CS7643 (deep learning) instead, which covers a lot of the modern NLP architectures in more depth and has amazing TAs. Rating: 2 / 5Difficulty: 3 / 5Workload: 10 hours / week - HAguuo5dzJMJGPaXXeclcA== March 22, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) Hmm, I am feeling rather ambivalent about this course as a whole so far. The lectures by Dr Riedl were fantastic, and they have helped me gain a much better understanding of tricky NLP models like transformers, seq2seq, LSTMs etc and the lecture content was presented superbly by the professor. The same cannot be said for the Meta lectures unfortunately. The saddest part about this course is mainly in relation to the rather vague and questionable option choices given as part of the quizzes and exams. Some of the questions had typos which led to a complete mismatch in expectations of the required answers between students and the grading rubric, while quite a few of the quizzes tested definitional questions using vague options which defeated the purpose of assessing a student's knowledge for the content. I would say that the course would be in a much better shape if the quizzes and exam questions were more polished in terms of precision. I understand the intent behind the vagueness (defeat the use of LLMs) but given the closed book nature of the exams, perhaps having questions that were more directly worded can make the test taking experience and assessment of knowledge more pleasant and accurate. Rating: 3 / 5Difficulty: 3 / 5Workload: 8 hours / week - awYgiOyV8rynxZPMkPOQoQ== March 22, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) Whoever is leaving the 1/5 reviews is just mad because they did poorly on the exam because they didn’t prepare enough. Part of taking a graduate course is acting like an adult and taking personal responsibility for success and failures. This person flamed out in the ED forums, was disrespectful, and acted like a child. Do not pay attention to their reviews — Dr Reidl is great, the TAs were helpful and accommodating. More importantly, the material was very interesting and well explained. pS grow up Anonymous Duck. Rating: 5 / 5Difficulty: 4 / 5Workload: 12 hours / week - V3zNSIx3Ly3kbWC2XYV9NQ== March 19, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) The exam design is atrocious. Between the irresponsible TAs and the word games posing as questions, this course has become a complete train wreck. The TAs are obsessed with multiple-select questions—one even had eight options! I honestly suspect these were AI-generated. The TAs should really try taking their own exams before subjecting us to them.The exam design is atrocious. Between the irresponsible TAs and the word games posing as questions, this course has become a complete train wreck. The TAs are obsessed with multiple-select questions—one even had eight options! I honestly suspect these were AI-generated. The TAs should really try taking their own exams before subjecting us to them. Rating: 1 / 5Difficulty: 5 / 5Workload: 10 hours / week - Xufos/FC+l9HofxMOEzTTA== March 13, 2026 fall 2025 [Machine Learning for Trading](https://www.omscentral.com/courses/machine-learning-for-trading/reviews) Overall I liked the material of this class although I have to admit it just reinforced that algorithmic trading is a complete losers game unless you are one of the big quant firms. My one complaint is I got a 20/50 on one project because I used a table instead of a graph, and I had two of my paragraph headings swapped. This dropped my grade by about 5% which was pretty lame. I felt like the grading much like many OMSCS classes is subject to capricious and highly variable graders. Rating: 3 / 5Difficulty: 3 / 5Workload: 8 hours / week - LdUCwaravOrZ37Up9FutNA== March 11, 2026 summer 2025 [Digital Marketing](https://www.omscentral.com/courses/digital-marketing/reviews) This has to be the easiest course in the program. The entire course is opened up immediately. It took about 2 1/2 weeks to comfortably complete the entire course. My only two pieces of advice- 1. Read the requirements for posting. I believe people got 0s on simple posts because they didn't bother to follow the basic rules of what not to do. 2. Put some effort into preparing for the exams. They're relatively heavily weighted. I did not do well on the midterm because I did 0 studying. Then I put in a little effort on the final and cruised. You will not get a study guide for either test (yes, even if you wait for the "scheduled" test week) so you'll have to review everything for that half of the course. After that, just monitor your email every week or so to watch the grades roll in. Rating: 4 / 5Difficulty: 1 / 5Workload: 2 hours / week - LdUCwaravOrZ37Up9FutNA== March 11, 2026 spring 2026 [Computer Networks](https://www.omscentral.com/courses/computer-networks/reviews) I came in with network experience, so the first few weeks weren't terribly exciting or new for me. However, if you are new to networks, I think the information can help understand what's going on behind the scenes. The TAs were available throughout the course. There was a lead TA for each project and they took the time and effort to make interesting problems to solve. I would recommend decent Python knowledge if you don't want to struggle mightily with the projects. Nothing dramatic, but understanding inheritance will go a long way. The lectures were an abomination. The slides were fine and provided information. But the actual recorded video may have been recorded during a hostage situation. It was not motivating. And the professor popping up twice - once before the midterm and once before the final - to review quiz questions that aren't related to the exam didn't seem terribly useful. The least interested person in the class should not be the professor. The exams were a minor annoyance. If you went through the slides you'll do fine overall. Overall, there were interesting parts to the course. Rating: 3 / 5Difficulty: 2 / 5Workload: 8 hours / week - FNSkyjhjdkDAZ1hbqpRZkQ== March 11, 2026 fall 2025 [Reinforcement Learning and Decision Making](https://www.omscentral.com/courses/reinforcement-learning-and-decision-making/reviews) Check out the grade distribution, this class has gotten worse, people are getting more Cs and Ds now. Not recommended for people with a full time job. I was counting on "the curve" to get a C and graduate as it was my last class. There wasn't any curve that people speaks of during Fall 25. Office hours was a waste of time, lectures was useless. I should of use PPO for everything and it would of make my life much easier, but I chose to experiment with different algorithms. You will learn absolutely nothing from the teaching staff. Count on reading a lot: Sutton RL book end to end, MARL book, and the Grokking book for the algorithms. What you paid for is for someone to read your papers and give you a bad grade because you didn't meet their hidden rubrick. I dropped this course twice before during the registration period. I finally decide to go with it thinking the new staff is better. BIG MISTAKE. I got to take a 11th class now. Rating: 1 / 5Difficulty: 4 / 5Workload: 30 hours / week - Q7vQ4S8LzdYPLTOEp+OplQ== March 10, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) Wish I could enroll for only half the semester. Rating: 1 / 5Difficulty: 5 / 5Workload: 19 hours / week - wzuTgVDUXQlOr0c6l20xdw== March 7, 2026 fall 2025 [Introduction to Health Informatics](https://www.omscentral.com/courses/introduction-to-health-informatics/reviews) Very easy course. Projects weren't time consuming, quizzes were open note, no Honorlock either. Got an A with no struggle. Final project was a little difficult, it really depends on who you get for your group members. But don't slack off, or otherwise you'll be spending multiple hours a day trying to get all the deliverables done as the course finishes. Rating: 4 / 5Difficulty: 2 / 5Workload: 4 hours / week - Q7vQ4S8LzdYPLTOEp+OplQ== March 6, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) Had so much fun with the exam and Meta lecture. Rating: 1 / 5Difficulty: 5 / 5Workload: 15 hours / week - RwC4XfLWS/UqhqfB5w2qFA== March 3, 2026 fall 2025 [GPU Hardware and Software](https://www.omscentral.com/courses/gpu-hardware-and-software/reviews) The GPU HW/SW course is a well-balanced class that provides hands-on experience with both GPU programming and GPU microarchitecture, along with a bit of compiler-style dataflow analysis. The workload is moderate, the projects are well-scoped, and the TA team is exceptional - making it a strong elective for students interested in systems, architecture, or parallel programming. Projects The course is built around five projects, each highlighting a different part of the GPU stack. Project 1 – CUDA Matrix Multiply (Intro Project) This is a basic introduction to CUDA and the ICE cluster environment. The assignment is just a warmup to get familiar with the toolchain and cluster workflow. Anyone with basic C/C++ experience should complete it quickly. Project 2 – Bitonic sort in CUDA This is the toughest project, but also the most rewarding. You implement Bitonic sort in CUDA and optimize for performance. The optimization component adds some challenge, but the project is very doable and well-defined. Many students consider this the highlight of the course. Projects 3 & 4 – GPU Hardware Simulation These were two separate assignments where you modify a simplified GPU simulator to explore architectural concepts like: -modeling GPU cores -adjusting pipeline/latency behavior -experimenting with warp scheduling strategies These projects aren’t conceptually difficult, but matching simulator output exactly can be tedious. Fortunately, full precision matching is not required; you receive 95% credit as long as your statistics fall within a small tolerance. As of the current semester, these two have reportedly been merged into a single Project 3, and a new Project 4 has been introduced related to ML (attention mechanisms). I don’t have specific details on that new assignment, but historically the simulator projects have been very manageable. Project 5 – Dataflow analysis (Reaching Defs & Liveness) Despite the terminology, this is not a compiler-heavy project. You analyze a small set of instructions and compute reaching definitions and liveness information. Students without compiler backgrounds typically do fine. It’s systematic rather than difficult. Lectures, Quizzes, and Exam The lectures are (very) short and focus directly on the material needed for the projects. They are not exhaustive or deeply theoretical, but they give you enough context to succeed. Quizzes are straightforward and (at least previously) open book. There is one final exam worth 10% of the grade. It was fair and consistent with the quizzes and lectures. There is a policy requiring at least 90% overall, and at least 40% on the final exam to earn an A in the course. TA Support The TA team is one of the strongest aspects of the course. The head TA (Scott) is exceptionally responsive, and the entire team is helpful, knowledgeable, and engaged. Ed support is fast and detailed, which significantly improves the project experience. Workload & Overall Difficulty Overall, the effort level is medium to medium‑low (likely medium now given the new project,which probably increase the course load by 15-20%). The projects are interesting, the course is not stressful, and the pacing is comfortable. It’s a great “systems” elective that blends GPU software, architecture, and light analysis without overwhelming students. Final Verdict Highly recommended! Especially for students interested in GPU programming and architecture, and performance analysis and optimization. The course offers a meaningful hands-on experience with a manageable workload, excellent TA support, and projects that are both fun and practical. Rating: 5 / 5Difficulty: 3 / 5Workload: 12 hours / week - VCDIClRtIFtPSzHF+7M+iA== February 28, 2026 fall 2025 [Advanced Internet Computing Systems and Applications](https://www.omscentral.com/courses/advanced-internet-computing-systems-and-applications/reviews) https://www.ratemyprofessors.com/professor/1651694 The reviews on ratemyprofessors matches my experience in the class. Writing heavy (8 pager every week). Unclear rubric and flags you for AI even if you didn't use AI. Professor does not care and says Canvas' AI detector decision is final. Leading to a situation, where it is better to have grammar/spelling mistakes in your paper to have a lower chance of getting flagged. The grading criteria for assignments is extremely vague and the feedback you get from course staff is surface level. Rating: 1 / 5Difficulty: 4 / 5Workload: 15 hours / week - fCzz1wtfcs0nTjWI8fFOxw== February 23, 2026 spring 2026 [Machine Learning](https://www.omscentral.com/courses/machine-learning/reviews) I took (and withdrew from) this class as my 6th in the program. I was taking this course as an elective. Don’t do it\! This course is awful. The assignments might be worthwhile exercises if you already know ML, but otherwise it’s more like busywork or hazing. In a single report, the timeline for which is about 3 weeks, you must implement then “analyze” and discuss several different models on two datasets. This could be useful, except the course content does not at all prepare you for what’s in assignments. Thus, in order to be able to somewhat genuinely write on these topics, you must spend hours and hours researching outside of the course content to get a handle on what the assignment is asking you to do. Then, you must implement these models, which might take hours to tune/run, and write a report discussing all of these topics you have to self-study. This genuinely could work as a fruitful learning experience, except you’re also burdened with quizzes and an exam. These are more closely related to the course content, but again totally disjointed from the assignments. So, in the same 3 week span, in addition to the time you must spend on self-studying for and working on the report, you must watch lectures/read/study in preparation for the proctored unit quiz. I submitted the first report, having spent \>40 hours on it, and felt like I hadn’t learned anything. My writing felt like slop, just BS I put down to get through the assignment. In every other course I’ve taken thus far, whenever I finished a very difficult assignment, I felt a sense of pride, achievement, and fulfillment. Not in ML. Rating: 1 / 5Difficulty: 5 / 5Workload: 40 hours / week - 4YpbCjbYv2B3IvKU2aXZhg== February 23, 2026 fall 2025 [Data Mining and Statistical Learning](https://www.omscentral.com/courses/data-mining-and-statistical-learning/reviews) As others have pointed out, the lectures feel like a waste of time. The quizzes are also not that useful and closely resemble (and often directly replicate) the practice questions, so as long as you've done those beforehand, you should manage fine. I’m giving a neutral rating mainly because I found the homework and project enjoyable, which balance out the more mundane aspects of the course. The flexibility to choose your own topic and dataset makes the project engaging, and I got to follow my peers' train of thought through peer reviews (yup, there are peer reviews). Overall, the course builds reasonably well in terms of content and expectations, which is a decent follow-up to ISYE6501. Rating: 3 / 5Difficulty: 4 / 5Workload: 8 hours / week - 4YpbCjbYv2B3IvKU2aXZhg== February 23, 2026 fall 2025 [Special Topics: Data Analysis for Continuous Improvement](https://www.omscentral.com/courses/special-topics-data-analysis-for-continuous-improvement/reviews) Mixed experience. The course didn’t really feel like it met graduate-level requirements since the material was quite basic and introductory. I was also somewhat frustrated with how my final project went, since there appears to be a specific structure and response preference that leads to better grades - it could work out if you focus on more 'traditional' sectors like manufacturing/supply chain, but may get marked down if you do something a bit more unorthodox. I also don’t think the green belt certification is particularly meaningful in today’s context (may even be a red flag to have it in your LinkedIn). Rating: 2 / 5Difficulty: 2 / 5Workload: 4 hours / week - cwsy/21t9yRCKivsAqMLfA== February 22, 2026 summer 2025 [Advanced Internet Computing Systems and Applications](https://www.omscentral.com/courses/advanced-internet-computing-systems-and-applications/reviews) When I looked it seems like there's other reviews for this course but they don't show up? I didn't take the course I'm just aware that you should look up the professor on RateMyProfessor before you take their class. It's Ling Liu the current prof. https://www.ratemyprofessors.com/professor/1651694 4% would take again, nuff said. Rating: 1 / 5Difficulty: 5 / 5Workload: 15 hours / week - GOgTqGxWG9t1dh0dOQbgDQ== February 8, 2026 fall 2025 [Software Development Process](https://www.omscentral.com/courses/software-development-process/reviews) Overall grade: A (99.56%) Background: BS in Computer Science. 3 years of STEM work experience (not as a software engineer). Lectures: The lectures are still from Professor Orso, even though he has moved to a new college. The videos are very high quality, and I enjoyed listening to the lectures. The material is presented in an engaging way that makes it easy to follow. In addition, the instructors include a set of notes from a previous student, which were still up-to-date with the current version of the course materials from what I could tell. Exams/Quizzes: There are no exams or quizzes in this course. Assignments: There are 6 individually-completed assignments, 1 group project, and 1 individual project. The first 5 individual assignments are easy points. The 6th one is significantly more tricky - more like a set of mini puzzles. However, once you figure out the answer, you will know it is correct. I caution that a previous reviewer of this class mentioned something along the lines of "you will lose more points than you would gain if you attempt and fail the extra credit" is VERY TRUE. If you do not think you have correctly satisfied the extra credit on assignment 6, then just do not attempt it. Each assignment took approximately this much time to complete: 1. survey - less than 30 min 2. git - around 2 hours (the assignment has some tricky wording, so I had to re-do part) 3. java programming - 4-6 hours 4. simple Android app - 6-8 hours, most of my time was spent trying to compile correctly because my Android Studio version was newer than what the assignment supported. 5. UML diagram - 5-7 hours. 6. testing - 8-10 hours Group Project: I luckily got a very good team. I think it is partly because I had no experience as a software engineer, so all of my teammates were software engineers. We communicated regularly on a private Discord group and were able to split the workload evenly amongst everyone. Despite not having past work experience as a SWE, I have written code in my current job and have a BS in Computer Science, so I was able to contribute a good amount to the team. We finished each deliverable well before the deadline. I can see how having a bad group would significantly impact your enjoyment of this class. I feel very lucky to have had a group much better than any I had in undergrad group projects. Individual Project: There are 4 deliverables, one due each week. They each take a vastly different amount of time to complete, with some requiring a lot of work and others being very easy. I don't think I can give away specifics of what each deliverable includes, so without any descriptions of the instructions, here is approximately how long I worked on each portion: 1. 16 hours 2. 15 minutes to get 100%. Then another 2-3 hours attempting the extra credit (which I did not manage to complete). 3. 5-8 hours 4. 30 minutes Participation: In addition to the coursework mentioned above, there is also a group participation/collaboration grade (10%) and overall class participation grade (3%). My group participation grade was 99% despite all teammates agreeing that we each pulled our weight in the project. I saw another reviewer suggest that the TAs may have a hidden set of criteria they use to finalize your collaboration score - I'm not sure if this is true or not though. My overall class participation grade was 100% despite not participating on EdStem much. I was very annoyed at the spammy students who would 'participate' by chaining 20+ "Thank you"s at the end of someone else's post. I did not do any of that and only participated when I had something legitimate to ask, answer, or share that would contribute to the conversation and still earned a 100% grade for participation. Overall: I felt that the effort required to earn a high grade was low. Not much coding was required, and the code that was assigned was mostly trivial. In this class, I learned a lot more about the documentation developed in the process of creating large pieces of software, but I wish there were more assignments about these pieces of documentation since that was my main takeaway from the class. The only time we wrote documentation for an assignment was the group project, but it was split among various group members. I would have liked more of the documentation to be done individually. Rating: 4 / 5Difficulty: 1 / 5Workload: 8 hours / week - UPMquKZjOzk3B7vxhaaTkA== February 7, 2026 fall 2025 [Digital Marketing](https://www.omscentral.com/courses/digital-marketing/reviews) Really light workload, 5 hours a week is being generous. Class is well organized and they provide everything up front at the beginning, so you can theoretically finish the whole class in the first week. Only "difficulty" is the memorization required for the exams. I scored a C on the midterm, so for the final I made sure to create and memorize flashcards and be able to recite all of the terms from memory which got me an A on the final and thus the course. Outside of the exams, there are 5 case study responses where you ready a case study and analyze it and weekly discussion posts where you need to respond to their prompts and reply to someone else. If you're able to finish most of the coursework ahead of time you'll just need to make sure you respond to another classmate's discussion post to get full credit for that week. Also it's crazy that this needs to be said, but please create your own response for the posts instead of just using ChatGPT. Rating: 5 / 5Difficulty: 1 / 5Workload: 5 hours / week - rBAAprTd7n4xR3KjrheEEg== February 6, 2026 spring 2026 [Computer Networks](https://www.omscentral.com/courses/computer-networks/reviews) I came into this course with no formal experience in computer networking or network engineering since I needed a class for registration and the waitlist for the other courses didn't have much momentum. For me, I needed to play catch up in terms of assumed understanding of how subnet, NAT router, ports actually work to make sense of the modules. Content: - Pretty dense modules and you have to read carefully - Kurose book and the youtube channel are helpful if I get confused by the professor's explanation. There were a few times where I needed to reference Kurose book for a clearer explanation Projects: - Required an intermediate level of knowledge with Python. Should not be too bad compared to other classes like DL from an "amount of coding perspective" - If you leverage the resources provided and READ the specifications BEFORE diving into the code, you should be able to get full score on Gradescope Community: - The TAs are pretty available on Edstem. There are dedicated TAs for the programming projects, content Q/A and general office hours - For the projects, the TAs provide chat sessions where you can ask questions about the projects. I found going to these really helpful in coming up with a simple, sufficient approach for the project implementation. Also, the chat sessions are very underutilized, so you should attend these when the projects come out to get the most support. - The wider office hours from the head TA aren't really productive. It's just more of administriva and very limited questions are asked - Professor Konte releases module summary videos which help to identify what are the main takeaways from the module. I didn't see too much of Professor Konte in the live setting so far Some areas of improvement: - Please update the documentation for how to setup mininet. Turns out the documentation provided in the Ed megathread was not accurate for Mac ARM processor devices. It would be nice to have a step by step video that's updated - The head TA doesn't really seem to answer a lot of questions. There are times where I asked a legit question in office hours and the head TA "shoots down the question". If you're gonna be helpful, at least answer the question or point in the right direction (eg: linking the edstem thread). Don't just answer every question with "that was clarified earlier". Most of the program consists of working professionals that also have lives - That being said, the project TAs and the content specific TAs are pretty good and clarify the doubts - Lower the weight of individual exams and increase the weight of the projects Rating: 4 / 5Difficulty: 4 / 5Workload: 12 hours / week - Gf7SwPsU9UURrDrapklYOg== January 29, 2026 spring 2026 [Secure Computer Systems](https://www.omscentral.com/courses/secure-computer-systems/reviews) It's unfortunate that this course is so terrible because it covers the kind of topics that I'm really interested in. Just like a lot of other reviewers mentioned, the quiz questions are poorly-worded and in some cases just plain wrong. It makes me wonder if whoever wrote the questions even understands the material themselves. This course isn't graded on a curve because it's difficult; it's graded that way because it's impossible to get a good grade when the test materials are unintelligible. I have no idea how a course could have so many complaints over a span of years and still not get fixed. TL;DR - This course is still a dumpster fire and it does not appear that there has been any kind of attempt to fix it. Rating: 1 / 5Difficulty: 2 / 5Workload: 10 hours / week - Bm6WunrnUMOeGi0X98AbfA== January 29, 2026 fall 2025 [Introduction to Information Security](https://www.omscentral.com/courses/introduction-to-information-security/reviews) This was an incredible course and Dr Wenke Lee is awesome. This class is basically a big CTF that is challenging, but they provide so much guidance and help, so it is still tough but very doable. I learned so much in this course, and they put so much effort into the labs and course material. If you are interested in cybersecurity, I cannot recommend it enough\! Rating: 5 / 5Difficulty: 3 / 5Workload: 10 hours / week - YJsqI0daonQZWcwuhRHNdA== January 27, 2026 fall 2025 [Artificial Intelligence](https://www.omscentral.com/courses/artificial-intelligence/reviews) Course has many interesting topics, TAs are helpful and this course has one of best TA support but everything else is made as confusing/hard as can be made. Each assignment has different number of gradescope submissions for no reason. Assignment 2 is not hard but you need an element of luck, that assignment works on gradescope for a small range of parameters. With limited attempts available, you have to be lucky to get it right even when your code is right. 6 attempts per 6 hours doesn't means 24 attempts in a day because most OMSCS students have job and need bare minimum sleep to survive. Basically, it translates to 6 attempts per day. Some other assignment instructions are made lengthy just because nothing should be straight forward. Focus in exams is on making them lengthy which leads to too many students seeking clarifications throughout the exam window. All this with MOOC level lectures. Overall, amongst most stressful courses in AI/ML specialization. Rating: 1 / 5Difficulty: 5 / 5Workload: 25 hours / week - UmpoA1qvCf95whP2KKtuNQ== January 25, 2026 fall 2025 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) For context this was my first course in OMSCS, and I come from a non CS background. However I have been working as a Software Engineer for 1.5 years when I started. I finished this class with an A. Pros: - Very very well organized class - Lecture videos are good quality - Projects were well put together, with clear instructions. Also felt like they did add to the learning. - Exams were fair Cons: - Don't get fooled by the mid-semester lull, where there's not much going on. Use it to study even harder for the finals. - Papers and some of the examples are based on older systems, might've been nice to explore the newer stuff. Rating: 5 / 5Difficulty: 3 / 5Workload: 16 hours / week - wWrNs/uhatb6su3iGfThYQ== January 25, 2026 fall 2025 [Introduction to Computer Vision](https://www.omscentral.com/courses/introduction-to-computer-vision/reviews) This course does a good job of exposing you to the fundamentals of CV. It’s not teaching you the latest techniques, but giving you the foundations on which they were built. I think it was a very good introduction class. It was my first class in omscs, so I did not really know what to expect. The assignments being due every 2 weeks ended up functionally meaning I would relax one weekend, then cram as much in the next weekend as I could. I found each assignment took me 15-20 hours on average, with the first one being easiest. The final project took me a very long time to complete, and I did not sleep much for two weeks while working on it. But, it was graded fairly. And the final exam was very easy - multiple choice, open note, open internet. I came into the class with experience working in python, and have used some opencv at work, but was still mostly reliant on LLM assistance for that. I come out of the class with a good foundation, I am glad I took it, and glad I wrestled with the material without relying on LLM code. Rating: 4 / 5Difficulty: 4 / 5Workload: 10 hours / week - KFCJslwPK2AlwJx/yRczvw== January 23, 2026 fall 2025 [Introduction to Analytics Modeling](https://www.omscentral.com/courses/introduction-to-analytics-modeling/reviews) TL; DR for ISYE 6501: Interesting lecture material + homework (15%) and project (8%) with work potentially sabotaged by peer grading. Horrible exams (75%). Some of the exam questions were so oddly worded that if English was not your native language you were at a distinct disadvantage. Enrollment: 1300+ students! Class subject matter+ HW assignments + project: 5/5 Peer grading and exams: 1/5 Overall course rating: 3/5. Exams and peer grading are red flags. Grades: HW + Project 100, Exams (average) 87, Final grade A (90%) Pros (Top 3): 1. Excellent choice of topics and covered in just enough detail by Dr. Sokol in well-organized lectures. 2. Interesting homework assignments, designed with the lectures in mind. HW consists of 80% of your time in this class and where you will put work in. This course needs to use the auto-grader for the coding. 3. The project assignment allows a deep dive into a particular problem and requires you use at least three of the methods acquired in the first 10 weeks. As with the homework you get out of the project what you put in. Cons (Bottom 3): 1. Exams: 75% of Grade. It’s a shame that the often ambiguous and poorly worded exams account for 75% of the grade in this course. Many exam questions introduce an unnecessary level of ambiguity that is unsettling. 2. HW: Homework and Project (23% of Grade) are all peer graded, and account for almost a quarter of the grade. Some of the peer reviews I received were performed with only a modicum of effort if any. Given the quality of gatech.edu as an engineering school, the lack of an auto-grader for coding exercises is unforgivable. 3. Office Hours (OH): Due to work pressures I had to finish the HW well before OH on Monday. So, OH were not very useful. As reported in OMS reviews, some students waited for the office hours the Monday before the HW was due and then copied the work done there. Some of the HW rubrics were weak and nearly incomplete. Six course design fixes that would allow ISYE 6501 to achieve a 5/5 rating: 1. Exams: Make exams better reflect the material not the ability to dissect triple negatives and split infinitives. 2. Grading: Please reward work on homework writeups. At minimum a 50%-50% split between HW/Project and Exams. 3. Coding: Include a 5-10-minute TA-led segment demonstrating R or python code relevant to HW as part of the lecture. 4. HW: Implementation should require the student to deep dive the details. Provide more test problems. 5. Require 2+ of the HWs (chosen randomly) to have one TA grade to ensure quality grading & identify poor peer graders. 6. Get rid of Piazza, use Ed. Rating: 3 / 5Difficulty: 3 / 5Workload: 15 hours / week - 5KFaeI5zlX6a7rXzBbKy1w== January 18, 2026 fall 2025 [Data Analytics and Security](https://www.omscentral.com/courses/data-analytics-and-security/reviews) I received an A in the course, however it is an extremely badly organized course by the professor and especially the head TA. The course content is also just basic statistics and an intro to Python and R course. Assignment and project instructions are extremely vague, rubrics that are given are not the standards that the TAs mark with according to both the professor and the TAs. According to the head TA Emma Kathryn Shumway, she's been working as a TA for this course for 10 semesters. The course still being this badly organized with the exact same problems that other reviews have discussed years ago shows that the problem is with the professor as well as whoever is leading the TAs (probably the head TA). The head TA also deducts marks for things that she said was acceptable on Ed discussion, and when brought up she refuses to adjust marks accordingly. When asking private questions on Ed discussion about projects and assignments, myself and multiple other people that I've talked to have been ignored. The professor, Dr. Borowitz seems nice during office hours, but over the semester I sent him 3 emails regarding assignments or projects and he did not respond to a single email. Overall I have to say this course is the least organized and the most frustrating course I've taken at Georgia Tech. Rating: 1 / 5Difficulty: 2 / 5Workload: 8 hours / week - zTGtCcoUrbslUl/F5gCtgg== January 17, 2026 spring 2026 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) Spring 2025. Way more time consuming than it is worth imo. Really good lecture. Shit load of busy work. Do not walk into this expecting an easy class. Low brain power? Yes. Multiple things to do every week? Also yes. If the entire course was like the first half that would be great, but once the lectures stopped the course kinda went downhill. Less busy work and this course would be awesome. If this is the only course you are taking, then 5/5 great class. I just found it stressful to handle so much extra work because I was taking 2 classes this semester. Rating: 2 / 5Difficulty: 2 / 5Workload: 15 hours / week - zTGtCcoUrbslUl/F5gCtgg== January 17, 2026 fall 2025 [Deep Learning](https://www.omscentral.com/courses/deep-learning/reviews) I was so burnt out taking this course. Please do not double up on this one. Somehow got an A at the end, but did not learn as much as I wanted because I was so tired by the end. Covers an insane amount of content. Grading largely via auto-grader so not as vague as something like ML. However, performance is a portion of your grade (do not take this class if you dont have a GPU), and there is honestly not very much room to really experiment with ideas because everything is so clearly laid out in the autograder. You will know that a lot of things EXIST, but not actually understand them. Regardless, a good survey course for that. You will be forced to learn a lot, just not that deeply imo. There is a group project. It is graded very easily. Honestly you can probably get an A on this doing a solo project if you needed to. Pick something interesting and don't worry about getting good results. Find team-members early. Pro Tip: Give up on the quizzes, the ROI studying for them is not there. You should be getting an A on every assignment if you just put in the work. If you put in the hours you WILL do well. I spent significantly more time on this course than ML (took over the summer) on a per-week basis. Rating: 4 / 5Difficulty: 5 / 5Workload: 20 hours / week - zTGtCcoUrbslUl/F5gCtgg== January 17, 2026 summer 2025 [Machine Learning](https://www.omscentral.com/courses/machine-learning/reviews) Amazing course. Time consuming. Great 'professional DS' simulation if you are interested in that career. Don't overthink the assignments. I spend way longer on the first few, but didnt really get a better grade. Try to timebox to 20 hours - 30 or 40 at the absolute max. Try to start at least the weekend before they are due (2 full weekends to work on the project). Rating: 5 / 5Difficulty: 3 / 5Workload: 18 hours / week - zTGtCcoUrbslUl/F5gCtgg== January 17, 2026 spring 2026 [Applied Cryptography](https://www.omscentral.com/courses/applied-cryptography/reviews) Taken Spring 2025. I studied math in undergrad. Made this a lot easier. Would be a 5/5 except the TA and grading is honestly a pita. It is extremely unclear and thier definition of a 'proof' and what can and cannot be assumed is very misguided tbh. A lot of the problems are left extremely vague and you arent allowed to ask questions, but you are punished for making the 'wrong' assumption. I literally wrote down 2 possible solutions based on 2 different assumption sets for a vauge problem, and was marked down on BOTH solutions (one was 'incorrect assumptions' and the other had a small syntax mistake). This completely defeats the point of a proof based assignment - you should be assessing the logical reasoning and deductions not weather we can guess what you want for a given problem? No cryptography background needed for this course. This course was not exceptional but not bad either. If you want to learn how to do proofs this, albiet not the best avenue, is probably your best shot in this program. Rating: 4 / 5Difficulty: 3 / 5Workload: 10 hours / week - QXVJyKsMsSwQ8RZ4khjCCw== January 16, 2026 fall 2025 [Knowledge-Based AI](https://www.omscentral.com/courses/knowledge-based-ai/reviews) I don't really get all the complaints about this course. Some on reddit said "this is the worse class ever" while others on discord were saying that it was BS...uh...were we taking the same class? I guess one valid complaint is that the lessons aren't very applicable to industry, but like, that describes 70% of the content in this master's degree (except for GIOS, that class was amazing). I thought the class was pretty decent, even good at times, actually. Like sure, it's a David Joyner class so it will have a fair bit around of busy work but overall expectations were very fair and the homeworks and projects were pretty relevant and reasonable. I thought the course was altogether quite easy especially compared to summer ML4T and the TAs were very helpful. I wasn't a big fan of the lectures but some of the projects were fun and relevant. I personally reused my decision tree code from ML4T for one of the miniprojects and you got introductions into important algorithms like A\*, DFS, BFS if you chose to use them for the miniprojects. The new ARC-AGI project was also pretty fun and while some say it was harder than the old raven's projects, I thought it was very reasonable so long as you don't procrastinate. One key thing to note is that you get points for the training problems too, so literally you are guaranteed at least 50% of the code portion of the points if you aren't lazy. Some complained about the TA grading but I didn't have any issues and got literally a 100% for every written assignment I submitted. All I did was open the rubric (there should be a table rubric for each assignment) and I wrote to the rubric. Put my subtitles in my paper as the exact same row name in the rubric and wrote to the rubric, and I never had a problem with grading. Heck, I thought the grading was more lenient than most of my undergraduate classes. Seriously y'all. Were we even taking the same class? Overall, 10 to 15 hours a week for this class as long as you are consistent. Pretty moderately easy. I think hardest parts were a few of the mini-projects and milestone D of the ARC-AGI projects, but if you do well enough on the mini-projects you can afford to half-heartedly address milestone D. Rating: 4 / 5Difficulty: 2 / 5Workload: 15 hours / week - \+P2SNPgxTxx8N5phkJLrpA== January 16, 2026 fall 2025 [Knowledge-Based AI](https://www.omscentral.com/courses/knowledge-based-ai/reviews) This course was my first OMSCS class. I came away with mostly positive feelings about the class. For starters - Dr. Joyner and the TA we excellent. They were super responsive, engaged, and enthusiastic. I think that the decision to migrate the semester project to ARC-AGI from Raven's Progressive Matrices was awesome. I appreciate how much work that must have taken - and I feel that it greatly enhanced the learning experience. Another positive aspect of the course is how well organized it is. It is clear from Day 1 exactly what you need to be successful in the class. Everything is available from the jump and this would be a great class to work ahead in if you wanted to. There are many assignments throughout the semester. While this can be a bit grating, or feel like busywork at times, they were generally interesting. And opportunities for easy points. Sometimes other reviews for other courses discuss being annoyed with the uncertainty - and I feel like this class is the antithesis of that. The lectures I found interesting at times. Unfortunately, they didn't feel as "rigorous" as I wanted them to. I feel like there are more abstract topics in computer science (like algorithms) are theoretically/mathematically well founded. Or there are more practical classes (like Operating Systems) which are grounded in their practical application in the real world. KBAI feels like a course discussing a particular view of artificial intelligence which is neither mathematically "true" nor broadly in use. It is a very "vibey" class which kinda left me feeling like I was not learning a "real" computer science topic. Some people in the class complained about the peer review software or some of the other administration of the class - but that never felt like an issue to me. Also - people who were complaining about not getting perfect scores on the assignments seemed to be missing the forest (an A is extremely attainable in this course) through the trees (missing 5% due to poor formatting on a report without comprehensive enough TA explanations). In summary - I think this is one of the best ran classes I have ever taken. It really does not waste your time teaching you the material along the way. Ultimately - the subject matter / topic did not completely resonant with me. Which colors my rating + feelings of the class. But depending on what you want out of it - it could be a perfect class. Rating: 4 / 5Difficulty: 3 / 5Workload: 8 hours / week - dOsCVsfzgP02nQrTuuIGGA== January 14, 2026 fall 2025 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) excellent course\! Rating: 5 / 5Difficulty: 5 / 5Workload: 25 hours / week - cGGo8T2m8PqYVhqrIFO1ZA== January 14, 2026 fall 2025 [Database System Implementation](https://www.omscentral.com/courses/database-system-implementation/reviews) Lectures were useful maybe 50% of the time. Spent way too much time on c++ and not enough time digging into more internals of databases. I might just be too smooth brained, but I thought the exams were kinda challenging. Wording was strange at times, and I felt they took "practical application of course material, multiple choice, and not much written math" to its limit in difficulty. Some exam questions were on research papers that were provided throughout the semester. I found the topics interesting, but the reading load on them wasn't very balanced. TAs were slow to respond. Office hours were exactly once, 1 hr/week, which was bad, but always with the professor. The professor himself was one of the best parts of the class. Even though the lecture content was often not what I wanted to be watching, he's extremely happy to be talking about this material. During office hours, he was genuinely interested in hearing from students, helping where he could, and giving high-level overviews of the research papers. Rating: 3 / 5Difficulty: 3 / 5Workload: 8 hours / week - rBAAprTd7n4xR3KjrheEEg== January 13, 2026 fall 2025 [Data and Visual Analytics](https://www.omscentral.com/courses/data-and-visual-analytics/reviews) Pros: 1. Most of your grade is based on homeworks and team project so you're rewarded for the hands-on part of the course 2. Bonus quiz opportunities are there and pretty manageable if you are on the border 3. Unlimited Gradescope submissions for HWs, so you should easily be able to get majority of the points 4. Not too difficult as someone who has full stack software engineering experience Cons: Oh boy, there are plenty of cons\! 1. Team project experience was ok. I lucked out with getting a team where everyone contributed so peer evals were easy. I wanted to do an interesting project that wasn't some cookie cutter ML model thing, but the time constraint given from the course was limiting. My team initially operated with 1 month worth of time for the project, but due to HW 4 and the annoying reports to write, there was really 2 weeks of time towards building the project. Splitting the work helps, but still we had to pare down a lot of the scope and the final product was kinda lackluster. I recommend picking up Streamlit and the documentation is very good 1. HW 2 (the D3 one) was kinda annoying. The D3 library is very finicky to pick up and you had to match the exact HTML structure to the T in order to get the autograder points. I had scenarios where the D3 visualization was bad but passed the autograder. 2. Lack of opportunity to assess visualizations we create. For a course that's about data visualization and analytics, that piece wasn't really covered. How about add a section or multiple choice piece in gradescope where we have to write a few sentences about how an existing visualization can be improved based on the provided context 3. Professor was hardly present in the course. I'd like to see a little bit more of Polo in the picture Rating: 3 / 5Difficulty: 2 / 5Workload: 10 hours / week - 9uYS8I6w+YWG6eX6KLPahQ== January 13, 2026 fall 2025 [Special Topics: Global Entrepreneurship](https://www.omscentral.com/courses/special-topics-global-entrepreneurship/reviews) This was very helpful for those especially wanting to make a start up. The lectures are practical and the assignment is a semester long mock start up. I agree with the professor, the only way to learn business is to do business and this mock start up is exactly how to go about on making a business. It's great to pair up this class with another. Rating: 5 / 5Difficulty: 1 / 5Workload: 5 hours / week - fVbu3miGRDfqMltO4NgwHA== January 12, 2026 fall 2025 [Mobile and Ubiquitous Computing](https://www.omscentral.com/courses/mobile-and-ubiquitous-computing/reviews) Pros: ``` The content is interesting The lectures are really valid from a content perspective TAs are supportive most of the time Teachers are supportive and welcoming during office hours The quizzes are "ok". Some of the questions are "confusing", but I wouldn't complain too much about that. ``` Cons: The course is badly organized. There's little room to plan ahead. The course will be unlocked after the first week. On Canvas you'll see everything due for December 1st, however the real deadlines are different. This might cause some confusion. There are neither notes/written versions of the lectures, nor you can download the videos; usually I wouldn't complain, however I want to mention that on Canvas the video player is awfully small. Not sure if this is an issue for most of the people, it was for me. Individual assignments and Group Project are the worst part: There are two individual assignments. I won't share too much detail on the assignment itself, but I want to complain about the way it's proposed. We were given the assignment description and a template. The real issue is that the assignment description and the template differ on some points. Clearly one of the two wasn't updated but they still expected you to follow both, since the grading of the paper really depends from it. Let me give you an example without giving too much detail about the assignment itself. ``` Assignment description: go from A to B and print the number of seconds you took to go from A to B. Print the value on a chart. Then go from point B to point A walking backwards. Template description: go from point A to point B. Then print the result, then print the chart. Then repeat the steps, print the value, print the chart. Compare the two charts. Grading description (available only when the TAs evaluate your submission) will loosely match the template description, but not at 100%. ``` However, following both points is confusing, especially because the assignments description don't match at 100% and TAs have to give extra information, for example by saying which task has to be excluded from the submission. Why couldn't they just write an assignment that includes everything? Unexpectedly, the second assignment is incredibly well written and the requirements are clear. If you already took HCI, there's a lot of overlap with some core concepts and, in my opinion, most of that content is better covered by Dr. Joyner's class, at least from an organization and material standpoint. I understand that some people might be interested in taking this course rather than HCI, but I have to consider that this is a core course for the HCI specialization, so the overlap is almost certain in case you enrolled in this specialization. The poor course organization reflects into parts of assignments being postponed and/or canceled. Is not a bad thing, but it really gives you little room for planning ahead. There are few mismatches between Canvas grades and what's written on the syllabus, this is not really clear, my team and I might just be wrong, but it appears so. Up until now is the worst course I've taken. I don't know if I've been spoiled by the quality of previous classes, especially Dr. Joyner's, but is a fair course that's make awful by the lack of organization. Teachers and TAs try to make up for this by being really flexible and supportive, but wouldn't it be just simpler to reorganize the course for good? TL;DR Version Interesting content and solid lectures, with supportive instructors and TAs. However, the course is very poorly organized. Deadlines are unclear, materials don’t match (assignment descriptions vs templates vs grading), and planning ahead is nearly impossible. There are no written notes, the video player is tiny, and some quiz questions are confusing, not to increase the difficulty of the course, just badly written. Individual assignments and the group project suffer the most from inconsistencies and last-minute changes. Compared to other classes, the overall structure and clarity are significantly weaker. Instructors try to compensate with flexibility, but the course urgently needs a proper reorganization. Rating: 1 / 5Difficulty: 1 / 5Workload: 10 hours / week - sopEmb90N5ucEVVYW1g0wQ== January 12, 2026 fall 2025 [Deterministic Optimization](https://www.omscentral.com/courses/deterministic-optimization/reviews) I thought this was an excellent course. Even coming in with industry experience in mathematical optimization (LP/IP, commercial solvers), I learned a lot of genuinely new and useful material. The only real downside is the timing around the midterm—having a regular homework due during the main exam study week can be rough. Overall impression I genuinely think this is a great course. It’s well-structured, the topics are thoughtfully sequenced, and the class provides a strong foundation that is both academically solid and highly relevant to real-world optimization work. For context, I finished the course with an A. My background (so you can calibrate this review) I work professionally as a mathematical optimization / operations research engineer. In my day-to-day job, I build optimization models and solve them using commercial solvers such as Gurobi and IBM ILOG CPLEX. Before taking this class, I already had a working knowledge of linear programming and integer programming, so I did not start from zero. What I liked most: topic coverage and progression One of the best parts of this course is that it feels like it walks through the “standard” optimization curriculum in a clean and logical order—very similar to how a good optimization textbook would build up concepts from fundamentals. That said, even with my background, I still found a lot of value because the course includes advanced (but very practical) topics that I had not studied deeply before. Examples include: • Transforming certain robust optimization formulations via duality (and seeing how they can reduce to more standard planning formulations) • Dantzig–Wolfe decomposition and the underlying idea of decomposing large structured problems • Actually getting hands-on exposure to column generation, which I strongly believe will translate directly to real industry projects Nonlinear / convex optimization coverage I also appreciated that the course doesn’t stop at LP/IP. It introduces the “entrance” to nonlinear optimization and convex optimization in a way that’s approachable and easy to follow. It won’t turn you into a convex optimization specialist overnight, but it does a great job giving you the core intuition and vocabulary. One thing I would improve: midterm week load If I had one critique, it’s the scheduling around the midterm. During the key week when you realistically need time to study for the midterm, you may still have a normal weekly homework due. That alone is tough, but what made it harder for me was that the homework around that time covered concepts that become very important later in the course. If your understanding gets shallow there due to time pressure, the second half can feel unnecessarily painful. So I don’t think the homework itself is “bad”—it’s important. I just think the overlap of heavy exam preparation + regular homework in the same week is a bit brutal and could be adjusted. Exams, pressure, and whether you should take it This course is definitely motivating: it pushes you to study seriously, and an A from this class really does mean you put in the work. Personally, I actually liked that aspect. In my case, I scored around 80% on the midterm, which put me under pressure to perform extremely well on the final. I ended up getting a perfect score on the final, and the process of studying under that pressure honestly strengthened my understanding a lot. So here’s how I’d frame it: • If you want an “easy A with minimal stress,” you might want to avoid taking this in a term when your schedule is tight. • But if you’re okay with a normal level of graduate-school intensity—and you want a rigorous, valuable optimization course—then I’d absolutely recommend it. Rating: 5 / 5Difficulty: 4 / 5Workload: 15 hours / week - SpcHYLG1mx3cm3W562UheQ== January 10, 2026 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) I thought that this was a great course that's very applicable to industry. The content was very interesting, even though it wasn't a technical course. The best part about this class were the lectures, as they were so well made. The readings were super interesting as well. There are three phases of this class: 1. The content phase: this is where you watch the lectures and complete 4 homework assignments, which are papers you have to write by answering four questions. 2. The practice phase: this is where you do the readings, complete quizzes on the lectures and the readings, complete test 1, and do the individual project. 3. The application phase: this is where you complete the team project and complete test 2. All in all, great course, although I missed learning more technical knowledge. Rating: 5 / 5Difficulty: 2 / 5Workload: 10 hours / week - yeBZMH1eU457toXtayf1WQ== January 8, 2026 fall 2025 [High-Performance Computer Architecture](https://www.omscentral.com/courses/high-performance-computer-architecture/reviews) I have no background in computer architecture not a computer science degree. I have exposure to OS and have been a professional SWE for 5 years. I found I had to catch up lots of hardware related topics that increased my weekly workload to 20 hours/week. Otherwise, it could be 10-15 hours/week. The material is great. Top notch, equal to the CMU course on YouTube. However, and I cannot stress this enough, THE PROJECTS SUCK\! You spend 5-10 hours tweaking parameters and recording perf. The end result is learning something obvious like "more cores = more overhead" or that "out of order execution order saves time". Really obvious information from the lecture that doesn't need repetition. I would have LOVED to implement some hardcore structures like writing a cache coherence simulation or coding reorder buffer logic. The most coding is ~50 lines of code to write LRU cache. This is a basic leetcode question. Not okay. I expected better. The course seriously needs a revamp here. I hope the professor reads this. Rating: 3 / 5Difficulty: 4 / 5Workload: 20 hours / week - kPRbSxTFjIkenr0EYxqjcQ== January 8, 2026 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) This course has a great professor who has a passion for the subject. Course was organized pretty well. There are two large projects broken up into small parts to make them digestible. The second project is a repeat of the first but in a group setting, which I didn't find valuable. The assignments are all written assignments (no coding). Rating: 4 / 5Difficulty: 3 / 5Workload: 11 hours / week - 7o5/Qgul8567CvjdgPz0Qg== January 8, 2026 fall 2025 [AI, Ethics, and Society](https://www.omscentral.com/courses/ai-ethics-and-society/reviews) This course is a good introduction to explainability and fairness in ML/AI. It is named the same as a conference called the AAAI/ACM conference on AIES which specializes on the same topic this course teaches. There is also a journal that publishes proceedings of the conference. I mention this because it gives students insight into exactly what you're signing up for. This is not a computer ethics class nor an AI ethics class in the pure sense. The "society" part is important because it takes a sociological lens and fairness here is understood in terms of bias against social groups. So once we understand the purpose of the class the material all makes sense. I docked a star because some of the assignments felt tedious, but I acknowledge it's hard to test for knowledge without some repetitive tasks. This is a highly important subject that is understudied and rarely used in industry but definitely necessary. Rating: 4 / 5Difficulty: 3 / 5Workload: 7 hours / week - 67SytxTnAw+4x2y4ZT4gvg== January 8, 2026 spring 2025 [Special Topics: Compilers - Theory and Practice](https://www.omscentral.com/courses/special-topics-compilers-theory-and-practice/reviews) This course was by far the most challenging I've taken so far at OMSCS. I came in with decent antlr knowledge from work experience .... I can only imagine what someone coming without that felt like. The final phase of the project was pretty brutal, I started early but still came down to the end. If you do not start early, you will certainly fail, the amount of hours to design/implement a solution is steep. You also often need to significantly refactor previous iterations of the project to accomplish the next step I found, which ate up a bunch of time. Rating: 4 / 5Difficulty: 5 / 5Workload: 25 hours / week - Fk0FQSMCiLF4JSvmuaGBhg== January 8, 2026 fall 2025 [Quantum Computing](https://www.omscentral.com/courses/quantum-computing/reviews) This class was really nice and interesting imo. I suggest it. Two exams, 4 labs, the exams are proctored which is annoying but I get why. Very informative class. Rating: 5 / 5Difficulty: 4 / 5Workload: 8 hours / week - QJfnPoFqMua2oeZuSZNI1g== January 7, 2026 fall 2025 [Computer Networks](https://www.omscentral.com/courses/computer-networks/reviews) I learned quite a lot from this course, mainly from reading the textbook and doing the projects. The lectures are fairly boring for many of them, especially when half of them are just paraphrased passages from the textbook. I strongly recommend reading the textbook, it goes a bit more in-depth and helps you understand all of the required materials. The quizzes are easy as long as you have a good understanding of what you just learned. The assignments aren't that bad, I finished them in half a day each project. The exams are completely fair. The professor is mostly missing the entire semester which is unfortunate but, it is what it is. Overall, good course, but lectures could be improved. Rating: 4 / 5Difficulty: 2 / 5Workload: 4 hours / week - QJfnPoFqMua2oeZuSZNI1g== January 7, 2026 fall 2025 [Deep Learning](https://www.omscentral.com/courses/deep-learning/reviews) This course taught me a lot about Deep Learning. Some of the lectures could be better and the Meta lectures are mostly awful; however, self teaching through other materials such as StatQuest or Stanford lectures are very useful. Do not bother reading the textbook, it is absurdly in-depth and is not useful. The quizzes can be studied for using the study guides the course staff releases, but even then, some of the questions on the quiz just make you go "what???". The projects are very interesting but can be pretty brutal. Good course. Rating: 5 / 5Difficulty: 5 / 5Workload: 25 hours / week - gJxd5E3NulatPmx8Q9V2AA== January 7, 2026 spring 2025 [Big Data Analytics for Healthcare](https://www.omscentral.com/courses/big-data-analytics-for-healthcare/reviews) Great class overall to take near the end of the ML spec. The final project is very well thought out with topics given to us to choose from rather than us cooking up topics. The final project is done in duos so its not that bad and it can be as hard as you want it to be. I learnt a lot building and training a model from scratch for the final project. The exam is easy if you go through the lectures. Rating: 5 / 5Difficulty: 4 / 5Workload: 15 hours / week - gJxd5E3NulatPmx8Q9V2AA== January 7, 2026 spring 2025 [Data and Visual Analytics](https://www.omscentral.com/courses/data-and-visual-analytics/reviews) Do not take this class. You will work in a group of 5 to do a project that one person can do in the Ai era. Although you will learn a bit about full stack dev and Apis and learning how to learn random things quickly. Rating: 3 / 5Difficulty: 3 / 5Workload: 12 hours / week - gJxd5E3NulatPmx8Q9V2AA== January 7, 2026 spring 2025 [Database Systems Concepts and Design](https://www.omscentral.com/courses/database-systems-concepts-and-design/reviews) One of the most useful courses in OMS that you can take. It will take a lot of teamwork to get through the project's early stages so be prepared. One of the TAs is great, responds within the hour to any questions you ask. Rating: 5 / 5Difficulty: 3 / 5Workload: 12 hours / week - XWsfAaR0RRg6WjjxRoF0Dg== January 5, 2026 fall 2025 [Introduction to Information Security](https://www.omscentral.com/courses/introduction-to-information-security/reviews) Coming into this course its important to understand 1) It is run by TAs 2) it is project based. The other reviews state this as well, so it should not be a surprise. It may definitely have been nice to have the professor more involved, and high-quality lectures related to the course content would have been amazing, but that is not part of the course. The projects in the class are structured as a CTF style assignemnt - for the most part, you are working to identify flags hidden in an application. You will need to download a VM for this, so give yourself time to troubleshoot that if needed. The projects are each created and run by teams of 2-4 TAs (easier projects have 2, others have more). There may be more TAs in the background, but I only interacted with 2-4 on ed discussion/office hours. For about 60% of the projects (including the hardest ones), the TA who did the bulk of the work creating the project has long left the position. My general gripes with the course - 1. The TAs are inconsistent - on one project, you may be actively corresponding with the TA who designed and built it, while on others, you are talking to TAs who are more "maintainers." 2. The quality of TAs - almost none of the TAs actually work in a cybersecurity role professionally - a lot of them are simply folks who took and completed the course previously. Some of them have been a TA for quite some time as well. A recurring theme, though, is that these TAs often have no professional cybersecurity experience, and cannot help/teach further than the projects. Most of these teams no longer have the creator of the project around, so a lot of answers to questions are "just figure it out" or "use your resources." It is pretty clear after the course that a lot of the TA's knowledge of cybersecurity does not go past what is taught in the course and is very surface-level. 3. Ed discussion moderation - as the 1 - 2 weeks you have for each project goes on, you notice TAs remove/redact less and less from posts (as the volume of posts naturally goes up). If I had just waited until closer to the deadline on a few projects, the answer is pretty clearly written on ed discussion. You can find details on individual projects in the other reviews and I generally agree with those. The course heads really need to take a look at the overlap between projects (half of malware analysis just felt like the web exploitation project) and the usefulness of some projects (Machine learning was a complete waste of time). Many of the projects are at least 3-4 years old and may not be as relevant (the log4j project, while interesting, was little more than a wrapper around a hackthebox lab). Rating: 2 / 5Difficulty: 1 / 5Workload: 12 hours / week - oEQOXEftcE6DcQclBrWoWw== January 5, 2026 fall 2025 [Distributed Computing](https://www.omscentral.com/courses/distributed-computing/reviews) To be honest, getting B on the course might be easy since getting 62% overall alr gives you that. About the latest review prior to mine, i don't think that the last project only costed 15 hours and you alr got 82%. I spend more than 50 hours, code hundreds to a thousand LOC and only got 72%, given that too many edge cases for different parts that were not initially accounting for, hence may need to redo certain parts. I have 4 years of experience in backend development with Spring, solve a thousand of leetcode problem in java, hence my coding ability in java with the Collection framework is not at the beginner level. Mid-term and Exam-wise, I think that it depends, you can still study hard but unfortunately get low grade since you may focus on slides, lecture videos while the exam questions focus on the original papers. In my opinion, you still can get A if you do the bare minimum for programing parts 3 and 4 which are the main culprits for student depression (5%/5% p0 + 10%/10% p1 + 8%/10% p2 + 5%/15% p3 + 5%/15% p4 = 33%/55%) while getting full marks for participation (5%/5%) and full mark for exam (40%/40%) since cut-off for A is 82%. Regarding the contents, i find the first half useful since it makes you reasoning things well and will sharp your mindset into thinking what failure models you may get into, what should be done to prevent that during your system design/technical discussion. The second-half is more about the case studies and does not leave much impression on me. Rating: 4 / 5Difficulty: 5 / 5Workload: 30 hours / week - r9dfALdlHDI51NbnofDZ3A== January 5, 2026 fall 2025 [Machine Learning](https://www.omscentral.com/courses/machine-learning/reviews) The concept of this course is interesting, but the execution is very flawed. Machine Learning focuses on the experimentation portion of machine learning. How do you interpret the results of a model? Is this model appropriate for this dataset? How do you verify a model's "correctness" for larger scale use? Unfortunately, the course itself isn't focused on teaching you how to go about doing those things. The reports that make up a bulk of the class work are entirely focused on interpreting and analyzing your experiment results. However, the class has no real introduction/lecture on the metrics that are commonly used or how to appropriately interpret models, leaving us to hopefully stumble into an effective teaching of these on our own. As of Fall 2025, we now have 10 - 20 page assignment docs - which provide *some* guidance into what metrics to look into by virtue of mentioning that a particular plot should be included, but even these aren't complete due to a lack of a formal rubric and additional instructions scattered on Ed. Only after the grades for A1 were out, and sample reports from other students were posted, did I get a better idea of what the "expected" interpretations/metrics were. This approach is certainly exploratory, but combined with the grading lottery others have mentioned, the lack of rubrics + scattered/unclear requirements, and the lack of guidance in appropriate exploration of a model... I found myself learning a lot less than I hoped, and instead spent most of my time guessing requirements and formatting LateX papers and plots to fit a strict page limit. Rating: 1 / 5Difficulty: 4 / 5Workload: 20 hours / week - ND4KfHYB+6idCR30DXEWWA== January 5, 2026 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) Marked the workload at 6 hr/wk but that's on average. There were weeks I spent 10 hours, and weeks I spent less than 3. I took this as my first OMSCS course because I heard it was well-structured and a good 'medium' difficulty entry point for graduate level classes. I agree with that. There's a detailed course calendar and all lectures and homework assignments are available at the beginning of the semester. The expectations for students are clearly laid out and I was able to work a week ahead, which helped a lot when stuff in my personal life got busier. I learned a lot and found the subject material super interesting. There's a lot of reading, so if you're a slow reader you may want to budget more time. The group project is kind of a waste of time (it's just the exact same thing as the individual project, but in a group), but I found a good group early and we did the project without any issues. The way the course is structured, you have to learn everything, do homework, take 4 closed note quizzes, and do a solo project in the first 11 weeks of the class. This is the part of the course that took me 10 hrs/week. Then, the last 5 weeks of the course is only submitting check-ins for the group project and taking 1 (open note) test. Since I had a good group, it took me 3 hours a week max to do the work required for the group project. Rating: 4 / 5Difficulty: 2 / 5Workload: 6 hours / week - GvorwXgJMs6F7hAO5LvZjg== January 4, 2026 spring 2025 [Introduction to Information Security](https://www.omscentral.com/courses/introduction-to-information-security/reviews) I achieved a solid A in this class and skipped doing the last assignment. Pros: Some fascinating topics. You learn quite a bit about foundational programming and computing topics. Things you are guaranteed to never use in your job, but you feel more accomplished knowing them, and are more well-rounded. Cons: If you find solving puzzles completely exciting, and being unable to solve some puzzles frustrating, this course will frustrate you. There were 2-3 assignments I couldn't figure out the final answer to, no matter what I did. I am confident that one of them was likely a bug in the assignment, but the TAs ARE NOT ALLOWED to help you. You either solve it, or you don't. I cannot overstate, you need to go into this class expecting that no matter how intelligent or accomplished you are, you may not solve every puzzle; AND be okay with not knowing why. Ha. Rating: 3 / 5Difficulty: 4 / 5Workload: 8 hours / week - GvorwXgJMs6F7hAO5LvZjg== January 4, 2026 fall 2025 [Data Analytics and Security](https://www.omscentral.com/courses/data-analytics-and-security/reviews) I achieved a high A in this class. Pros: Subject matter and quizzes are straightforward and do not take much time. For half of the semester, you can complete your week's work in about 1-2 hours. The course is heavily weighted toward the final project and paper. If you work on that consistently and early, the course is a breeze. If you have no experience in data analytics, its a great foundational course to get your feet wet. Cons: Some of the TAs' grading does not demonstrate competence. I spent around 80 hours on the final project alone because I wanted to really blow it out of the water. Those 80 hours do not count my teammates' contributions. And we received a B on our final project because the TA "significantly" did not follow the grading rubric. I found that quite frustrating and un-academic. I professional brought it to the TA's and the Professor's attention, and received no response. Many people complained about the TAs grading on the mid-semester project, and I can see why. Takeaway, I find that this class is overly weighted toward a complex, many-faceted, final project (30 page paper + 20 minute presentation) that is too complex for TAs to grade correctly. Rating: 4 / 5Difficulty: 2 / 5Workload: 4 hours / week - UGUoDfisXh5NauhtIFsIUg== January 4, 2026 fall 2025 [Artificial Intelligence](https://www.omscentral.com/courses/artificial-intelligence/reviews) This is an exceptionally difficult class. For context: I likely have more experience with Python than the average OMSCS student, but less overall CS experience. I took several related classes to prepare me for this one (KBAI, Game AI, AI4R, etc.), and it was still rough. But how difficult you find each assignment greatly depends on your familiarity with each section, and what your natural aptitudes are. Additionally, part of the difficulty comes from the strict plagiarism policy, which limits the external resources you can consult. Here's a breakdown of each assignment: A1 - A\*. ~60 hours if you haven't taken a graduate-level class that teaches A\* at a high rigor, ~20-30 with. Expect extra time if you want a 90%+. It took me ~40, and I found it to be the easiest assignment both to conceptualize and to program, despite most students saying that it's by far the hardest. The time investment comes from implementation size rather than conceptual difficulty. A2 - Game playing. ~40h if you're not comfortable with recursion and debugging complex recursive algorithms, ~20h with. I had a terrible time with this assignment due to misinterpreting the provided documentation, but otherwise thought it was conceptually straightforward. A3 - Bayes nets. If your understanding of graduate-level stats is solid, this assignment can be done in 5-10 hours. Otherwise, you're in for a rough couple weeks. I spent ~30 hours prepping for the assignment, and another ~30 on the assignment itself. This assignment requires a tenth of the coding of assignment 1, but it was far more difficult for me. A4 - Machine learning. If you're comfortable with numpy and vectorization, ~20 hours, ~40 without. This was the first assignment I felt that the provided material was not enough to understand the concepts, so I had to do a lot of self study. A5 - Gaussian mixture models. This is a very polarizing assignment. The first half requires what I thought was incomprehensibly obtuse numpy broadcasting and spatial reasoning, and it was easily the worst experience I’ve had in any CS class due to a complete mismatch with my aptitudes. The second half is comparatively trivial and doable in an hour or two. If you have strong linear algebra skills and a good working spatial memory, this will likely be a breeze. Otherwise, expect ~50 hours on the first half alone. A6 - Hidden Markov models. I didn't do this assignment, but the folks that did said it was on par with the difficulty of assignment \#4. Difficulty: A5 \> A3 \>\> A4 \> A2 \> A1 Time taken: A5 \> A1 \> A3 \> A2 \> A4 The midterms and exams are a great way to review and solidify your understanding of the material. However, you aren't really graded on your understanding of the material, but rather on how well you can solve dozens of problems without any mechanical errors. Being off by one decimal after 2 pages of math is worth 0 points, as is taking the right approach but making a minor mistake along the way. In addition, there are several ambiguously-worded questions and later-corrected solutions, and I found it to be a stressful experience. There's a 24 hour challenge period after the exam ends where you can argue your case for why your incorrect answer should be marked as correct. Expect your grade to jump as much as 1-2 letter grades (yes, 10-20%) after regrading. I asked for clarifications on a couple questions but was denied due to exam policies, so I had to guess between two answers, and later learned I chose the wrong ones. But overall, I found the TAs to be pretty generous and forgiving with points. Effort expended on exams does not necessarily correlate with a higher grade. Don't beat yourself up if you test poorly, it doesn't correlate with how well you understand the material. Lecture quality and usefulness varies. Some lectures were too high level, and others were better grounded in examples. I strongly recommend reading the textbook. I fully read or skimmed ~1000 pages throughout the course. I didn't personally find the discord helpful. Due to the plagiarism policy, most students are hesitant to share any tips, so it's better for morale-checking rather than assignment help. I recommend sticking with EdStem. The TAs are responsive and usually helpful, but they're sometimes hesitant to share concrete tips. Office hours are generally one on one, and I recommend joining those if you have questions or need a code review. If you're looking to prepare for this class, I *strongly* recommend these three things: brush up on A\*, learn how to debug (setting breakpoints, stepping through the code, etc.), and learn how numpy broadcasting works in 1D, 2D, and 3D. Linear algebra and calculus would help too, but I didn't struggle on those portions. And lastly: this review comes off as intimidating, because that's how I felt throughout the whole of the course. Conversely, I know many folks in discord who thought everything was review and never struggled at all. If you put in the time, you can get through this course. Due to varying assignment difficulty, I spent 10-50 hours/week on this class. Rating: 3 / 5Difficulty: 5 / 5Workload: 35 hours / week - vsibVbdFfYHQ84sN6cGhvw== January 2, 2026 spring 2025 [Digital Health Equity](https://www.omscentral.com/courses/digital-health-equity/reviews) This class has been available to OMSCS students for a while now but has not been on omscentral for some reason so I'll happily write the first review. I'm only now seeing on omscentral but I took this course a few semesters ago so i might be a bit hazy on some of the details. Professor Parker is very knowledgeable in her subject field which made all the lectures easy to understand. She records the lectures herself, so they are well made and seem relatively up to date. This is more of a do your research and write papers type of course and is not code heavy at all. You are given weekly lectures and readings about health equity. You will mostly learn about disparities within healthcare and how technology can be used to fight those disparities through the use of apps, websites, or other forms of technology. Based on these lectures and readings, you will write reports every few weeks ( i forgot how many, maybe 3 reports) and in between those reports you will develop 2 papers in which you design a prototype for a chosen health equity issue you wish to address. Throughout the semester, you will also work in a group on a specific project of your groups choosing. This can involve code but it can also be completely free from it. It depends on how your group wants to tackle it. This project has milestones which will need to be completed in addition to the research and design papers mentioned above which all make for a pretty writing intensive course. For our project we made a high-fidelity non-functional application using FIGMA so if designing is your thing, you'll enjoy this course. This class feels like a combination of AIES, Ubiquitous computing (only the good parts), and HCI. Overall, I enjoyed this course and would recommend it. Rating: 4 / 5Difficulty: 2 / 5Workload: 10 hours / week - vsibVbdFfYHQ84sN6cGhvw== January 2, 2026 fall 2025 [Introduction to Health Informatics](https://www.omscentral.com/courses/introduction-to-health-informatics/reviews) I actually really enjoyed the lectures for this course which were a highlight for me. Dr. Duke was able to bring together aspects of healthcare with technology rather seamlessly. I have a biology background, so this portion of the course was a welcome surprise. As others have said, this course can be divided into 2 halves. Lectures, quizzes, and labs in the first half and a group project in the second half. I enjoyed the lectures so I had no issues with the quizzes. The labs were pretty straightforward and for some of the labs you were completely guided through them by the TA's. Keep in mind though, that for some labs most of the time will be needed in setting up the proper environments which can be a pretty big headache for some people. But overall, I cant say I learned too much from them. The group project, as always has a lot to be desired. I was proactive and tried getting a group early on but was still left with teammates who did jack. Throughout the program, group projects have been my biggest gripe and one of my main sources of frustration. I don't understand how some of these people have jobs at FAANG or other giants and end up contributing so little. Anyways, I was able to get a high A but to say I learned a lot would be an overstatement. I enjoyed the healthcare aspect of this course way more than the technology aspect so there's some bias on my end. For the first half, I was on Ed discussion constantly but for the second half, I maybe went on once or twice a week. The TA's were great, some of the best in the program. They were quick to answer any questions and provide good guidance if needed. So the class was better than I thought it was going to be based on previous reviews but still not the best. Lectures: 5/5 Labs: 2/5 TAs:5/5 Project: 1/5 Rating: 3 / 5Difficulty: 2 / 5Workload: 10 hours / week - sjjStLXYWzrnvOb/j7kxvQ== January 2, 2026 fall 2025 [Data Analytics and Security](https://www.omscentral.com/courses/data-analytics-and-security/reviews) Join this course if you - want an easy B or C grade - Light coursework - Just care about passing, not really understanding anything Do not join this course if you - want a satisfying A - want to actually learn anything about cybersecurity - Have a low tolerance for bad TAs Having said that - here's my experience with this course 1. THIS IS NOT A CYBERSECURITY COURSE - This is a 100% STATISTICS course. Barring maybe a throwaway module on security concepts, the entire course is about statistics. Linear models, regression models, clustering etc and then implementing those in R. Final project is also pure statistics, finding some patterns and trends in data - zero cybersecurity. As someone with no interest or background in statistics this course was entirely awful - and I ended up just focusing on whatever needs to be done for grades. I didn't learn anything relevant or useful that could apply to any real world cybersecurity scenario. As a policy s 2. TA's will ruin this course for you - The assignments are vaguely worded, the rubrics are just as vague and the TA's make random judgement calls with no real recourse. Blanket "no regrades" are issued by TAs and the professor is hands-off, blaming students' grades on "low effort" (his words, in an actual Ed post). No reflection whatsoever that an entire class of 100+ students got bad grades and were complaining daily about TA's. Instead he blamed it on low effort. Students lost 5 to 10 points because TAs thought the paper had too many bullet points, or they didn't agree on where periods should be used, or they don't agree with the grammar structure or format of the write-ups etc. 3. Group project is a luck of the draw - you're paired against randoms for the group project. I had an awful experience with one person who literally did nothing (not even one word contributed to the final reports). The other one refused to hear any input and made the "group" project his personal project. Rating: 1 / 5Difficulty: 1 / 5Workload: 6 hours / week - 2Me+AQwmW5DaTYXjYAnU8g== January 2, 2026 fall 2025 [Time Series Analysis](https://www.omscentral.com/courses/time-series-analysis/reviews) It is a good class. The instructions are very detailed and the topics are interesting. If there are any improvements, it would be the question for projects can be a lot more clearer. Sometimes I had to input a lot more codes simply because what it asks for. Rating: 5 / 5Difficulty: 5 / 5Workload: 15 hours / week - MeZgjPPmk12++gjERVeq9g== January 2, 2026 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) This was my first course in OMSCS (Fall '25). I finished with a 96/100. I initially came into this course assuming there would be a lot of writing involved, and I was correct. You will write A LOT and as someone who doesn't really like writing papers, the classwork was not very enjoyable for me. With that being said, as long as you follow the instructions on the HW's and projects and base everything off of the course material you will get an A on them, they're just time consuming. The four quizzes are the hardest part of the course, but will also force you to learn the most. Each quiz consists of 5 essay questions - each with several different sub-components. They're fully proctored, no notes or outside help - just your memory. You're given two hours to complete them which is tough due to breadth of each question and the depth of your responses. It was also really difficult to digest any of the required reading material that you're quizzed on. Grading can also be somewhat inconsistent from what I experienced. The course is front-loaded like other people have mentioned. In Week \#9 we had an exam due, a quiz due, and a project check-In due. Once you've made it to this point - the rest is smooth sailing. Exams were proctored but open-everything. They are easy if you’re okay with a B on them - which I was. The projects (Individual & Group) are structured the same. If you follow all of the instructions and choose a good task/interface to improve you’ll be fine. The group project comes with all of the same drawbacks of any other group project. I was able to fulfill all of my class participation points by doing all of the peer reviews and taking some surveys for other classmate's projects. In short, the class is not inherently difficult it’s just time-consuming and requires a lot of writing. I found the material very interesting and the lectures very easy to digest. Dr. Joyner is so good at using examples to explain different concepts. Rating: 4 / 5Difficulty: 3 / 5Workload: 18 hours / week - CNFJRTK8LziCE4STdYeT/Q== January 1, 2026 fall 2025 [Machine Learning](https://www.omscentral.com/courses/machine-learning/reviews) This was my last course of OMSCS and the one that I was most worried about from reading the reviews on here. The course has seen major changes that have genuinely made it easier to pass the class. However, I still feel that this course doesn't do an adequate job of giving you concrete knowledge of ML. Pros: 1. Regrade Requests: The course has introduced the ability to correct issues found by graders for half points. So if you receive a 70% on a report and adequately address all issues highlighted by reviewers, then you could receive a maximum of 85%. I personally did not use this mechanic but others seemed to benefit greatly from it. 2. Quizzes: The quizzes allow for 1 sheet of notes and a calculator. You are also given multiple attempts. The multiple attempts alone made it extremely useful for me as I typically used 1 attempt to get a baseline of my current knowledge and gaps that needed to be filled. 3. Exam: The course has done away with the mid-term exam due to the workload of the reports to where we only had a final exam. The final exam is different from the quizzes and I'd argue is easier as it focuses more on concepts centered around the algorithms covered in the class. Cons: 1. Hidden and known rubric issues: In recent years, the requirements have become more clearly defined. You are told exactly what libraries you need to use, what plots are required, and given SOME details on how to structure the papers. However, the known requirements were honestly difficult to cover. For example, In A1 they required an absurd amount of plots and specified that they must be visible without zooming in. This forced me to drastically weaken my analysis just to include all plots. The known rubrics also went through MANY iterations and changes as the assignment deadline approached which I found frustrating. In A1 for example, the TAs defined a requirement, removed it, and defined it again in the span of a week. The hidden rubric also still exists and graders are using requirements that are not clearly defined when grading your assignment. 2. Grading delays: The grading was incredibly delayed and students had no idea whether they should continue or drop the class as grades for A1 did not come out until days before A2 was due (between these two assignments, that's 25% of your grade in limbo while the drop deadline was closing). The course also tells you that every report is iterative from the previous report in terms of the feedback that you receive. So you're expected to address feedback from A1 in A2 and the other reports. This didn't have a major impact for me and I only had to re-write small portions of my A2 report but this definitely affected other students. Additionally, I found it frustrating that regrade requests for A4 (the final assignment) were not available, with the stated reason being that grading delays pushed the timeline to essentially the end of the semester. Recommendations: 1. Reports: I personally got 92%, 99%, 100%, and 93% across all reports. You are given the option of doing extra credit for an additional 10% but with the already defined requirements, I found it difficult to manage the page limit as it is and opted out of doing the EC. My recommendation would be to clearly define the hidden rubric requirements as early as possible so that you do well on A1 and are not compromised on A2 with the grading delays. Ed Discussion and Office Hours were my main source of assessing the requirements. The TA's will not give clear answers and will give suggestions. I would treat those suggestions as requirements for your report. Also, the known rubrics will change over time so keep an eye on Ed Discussion for the latest version of these documents. I also think there is a disconnect on the purpose of these reports that is not adequately covered in the known and hidden requirements that trips up some students. The primary goal of these reports is to analyze the algorithms and their behavior on the provided datasets. The objective is not to maximize performance metrics or aggressively tune hyperparameters, but rather to explain why the algorithms behave as they do, interpret patterns and trends in the results, and connect those observations back to the underlying theory. Finally, I believe that completeness is valued more than accuracy which is unfortunate. I found myself constantly cutting or reducing my analysis to meet all of the requirements which made my analysis very light and surface-level. A4 was EXCELLENT in my opinion as it was light on plots and heavy on analysis. Overall, This course is clearly improving and It's clear that they're taking the feedback from previous semesters into consideration. However, I still think there is room for improvement. Rating: 4 / 5Difficulty: 4 / 5Workload: 12 hours / week - Hlbv1xErB9n1pHPQKEPY4Q== December 31, 2025 fall 2025 [Special Topics: High-Dimensional Data Analytics](https://www.omscentral.com/courses/special-topics-high-dimensional-data-analytics/reviews) ISYE 6525 - HDDA - is the first class I've taken at OMSCS that actually feels like what I expected when I enrolled into a master's level program. Lectures are short with no nonesense, and TAs will absolutely not hold your hand to guide you through the assignments. Coming into this class without knowing how to do matrix calculus and without being comfortable in numpy was tough. The first HW asked me to solve a linear regression without the professor explaining what a linear regression was. I was able to come arround and grasp the necessary material, but it's always frustrating when you realize you're paying money to self-learn. And even still, most of the assigned readings went straight over my head. There is no single textbook, but snippets of various (non-required) books and papers to read for each module. You'll have one module every 2 weeks for about 1 hour of lectures, 60 pages of text, and 1 HW. HW can be completed in Matlab, R, or Python, or any other language you choose, though example codes generously provided by the professor only come in these 3 languages. The 2 exams are essentially slightly tougher open book HW problems with 1 week less to complete them. Grading is extremely generous, actually insultingly so - I was frequently given full marks despite my code producing the wrong output. I found the lectures and the professor's style of teaching disappointing, and it seems most other reviews did as well. 1 hour's worth of lectures per 2 weeks is not enough for more than surface-level knowledge. It always bothers me when I hear a professor say "here's this formula. It can be proven to be accurate but I'm not going to show you how." You'll get a ton of that in this course. Don't expect to see proofs or derivations in the lectures themselves. This problem is compounded by the expectation that you will be using libraries to get your code to work (rather than implementing the algorithms yourself), so it'll be tough to grasp the details of what you're doing. Frustratingly, I sometimes found myself copy pasting the example codes without understanding how they work. Yet this was enough for an A. In summary: although the material was very interesting, I can't confidently say that I've learned it. Rating: 2 / 5Difficulty: 3 / 5Workload: 7 hours / week - Hlbv1xErB9n1pHPQKEPY4Q== December 31, 2025 fall 2025 [Applied Cryptography](https://www.omscentral.com/courses/applied-cryptography/reviews) CS 6260 - AC - is the most enjoyable class I've taken in the OMSCS program so far. Essentially what you'll be doing is taking the role of a hacker and try to break various presented encryption schemes. For the 2 exams and the 5 written assignments you'll be presenting theoretical hacks on paper, and for the 2 coding assignments you'll be designing and implementing hacks in Python. In other words, you will mostly be solving puzzles. So, you need to be comfortable with relying on your intuition and the provided examples - if you're experienced in playing Zachtronics or similar computer games you should be fine. The textbook is not required reading, but the professor is extremely clear and rigorous in her explanations, to the point where sometimes I would zone out of the lectures. Grading is overly strict - if you do not use exact language expected or do not fully show your work you will get points deduced, though you can dispute with the TAs. The cutoff for an A is at 80% score to make up for it. The assignments were very helpful in understanding the lecture content. I'm not giving 5 stars because the second half of the class (dealing with asymmetric encryption) had a noticeable drop in quality due to getting bogged down in the details of number theory. There was not enough time to cover the topic in depth, in sharp contrast to the first half of the class. Additionally, I wish we spent more time on practical applications and got to see real life examples. Finally, on the same note, the class did not seem to be rigorous enough for a master's level course. For instance, there were no (mandatory) readings assigned and we never had to prove that a scheme was secure (only insecure). Those of you who are privay concious be warned - you will have to install Honorlock spyware to take the 12 quizzes and 2 exams! Recommend using a live USB. Rating: 4 / 5Difficulty: 2 / 5Workload: 6 hours / week - zhE+Nal3x1LLOxyCcniiUg== December 31, 2025 summer 2025 [Database System Implementation](https://www.omscentral.com/courses/database-system-implementation/reviews) - This course felt like a beta course. It is not a graduate level course (I doubt if this can even be at undergrad level)! The content could have included other topics like Logging, Recovery, Transaction Management, Distributed and Cloud databases, Examples for the features described from modern databases but apparently another course is being prepared for these. If you are looking for a solid understanding of relational databases, just read the recommended book "Database System Concepts, 7th edition (https://www.db-book.com/) and may be go through Andy Pavlo’s youtube videos instead of taking this course. - As others said, too much time is given for C++ concepts in the lectures, thus depriving of chances to cover other database concepts. C++ must be made a pre-requisite instead. There is a programming assignment just to check C++ concepts, that could have been used for solidifying other database concepts instead. - TAs were mostly low key on Ed during the summer semester. They took many days to respond to student enquiries. I took a couple of courses before this, and TAs in this course are the least participating ones. Ed forum did not see much activity as the TAs and Professor didn’t respond to student queries within a few days in general (I would expect TAs to field most of the questions within a day or two). There was a time when all of them went completely silent for 4-5 days\! - Lecture slides contained many mistakes from the first run of the course and were not corrected in this run too. It seems like not enough attention or effort is spent to improve the online version of this course. If you are coming to this course expecting GIOS type of rigor and discipline, you’ll be disappointed\! - Exams and exercise sheets were not that challenging. Programming assignments don’t have much guidance via comments. However if you spend like 4-5 hrs per week, you can end up getting an A easily (assuming you have C++ knowledge). - This course’s curve is the most lenient (if you scored \>= 80% you get an A grade, otherwise a B) of all the courses. 90% of the students got A! If I knew this beforehand, I’d have studied even less for the exams and exercises and I would have spent more time in reading the book. Rating: 2 / 5Difficulty: 1 / 5Workload: 5 hours / week - 6v6NWG6Kl/hPv2eJJuS8gA== December 31, 2025 fall 2025 [Introduction to Graduate Algorithms](https://www.omscentral.com/courses/introduction-to-graduate-algorithms/reviews) I took GA as my last class, but having done that, I would recommend trying to take it a couple of semesters before you intend to graduate as I'm sure that would make it feel way less stressful. The levels of anxiety that GA can generate are really pretty nuts, so please take this advice seriously. It sounds strange, but other than the stress, I don’t really have a ton of complaints about GA. Brito and the TAs seem like genuinely nice and caring people, and I can’t really fault them for any of the negative aspects of GA. They seem to have experimented a lot over the years with how the class is run. They have incorporated student feedback, while still keeping the class rigorous and substantial. I believe they are doing their best. The exams felt mostly fair, and the grading was even generous at times. The only real issue I had was that it wasn’t always obvious what kinds of mistakes would result in massive point deductions and which would be treated more leniently, so I recommend getting as much clarification as possible about that from the TAs. Generally though, if I finished a test feeling pretty good about how it went, that was reflected in the grades, and if I felt like something went wrong, the grades reflected that too. I recommend attempting every single homework and practice problem that is assigned or mentioned in a post by the TAs, including the coding problems, and the extra practice problems. Doing that along with watching Vigoda's lectures and reading DPV should be sufficient to prepare for the exams. Before GA, I had previously taken ML4T, RAIT, ML, DL, CN, GIOS, HPC, HPCA, and Netsci, and I earned A’s in all of those classes. GA was my first B, and I missed an A by less than half of 1%. But I’m grateful that I got through it in one try and graduated OMSCS without having to repeat it. Rating: 4 / 5Difficulty: 5 / 5Workload: 24 hours / week - AsXSpPZZ36Buac6bbnSyRA== December 30, 2025 fall 2025 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) First class in the program, mech engineering bachelors from 10 years ago, some coding experience from the past few years of self-teaching. Overall, I learned a ton about how computers and operating systems work! I thought it was super interesting how applications interact with the OS, all the parts that make up an OS, and there was so much I learned about what goes on behind the scenes it made me in awe of computing systems. It felt like more than 17 hours a week. I would recommend starting projects ASAP and try to stay ahead of the schedule provided for the lecture modules. It helps watching the corresponding modules for each project before starting, so you should complete them before the project is even released ideally to avoid concentrating lots of those hours in heavy weeks. Projects - 100, 100, 110 Midterm - 77 Final - 93 Final grade - A Hours / week - 17 Projects Directly related to some of the chapters conceptually but you’re pretty much on your own to learn the coding. The time below includes the ReadMe write-up which I spent 8-12 hours on for each project. Project 1 - 70 hours. It took a ton of time for me since the only experience I had in C was from cs50 Harvard a long time ago. The warm up parts did a nice job of easing you into the main parts of the project though. It involved using sockets to send and receive data, then implementing parts of a provided library, then making the library multithreaded. Project 3 - 40 hours. It was the easiest by a lot in my opinion. Inter-process communication between cache server and proxy to serve requests to clients. Project 4 - 60 hours. This was the most rewarding but perhaps the most frustrating. You need to implement a distributed file system using gRPC. It took a really long time to understand all of the steps clearly but it was cool seeing it working and keeping all the files across all clients and the server in sync. I probably spend an extra 10 hours doing the extra credit. Tests The midterm was shorter and didnt include as much info as the final. I thought that both were pretty fair; there was a balance of facts and memorization with some questions where you had to apply your knowledge. I probably put in 15 hours for the midterm, and 30 for the final as I went through all my notes thoroughly, did a ton of practice calculations, made and practiced flashcards, etc. Lecture Modules (17 total) The lectures are really good and I only had to seek supplemental knowledge / clarification a few times over the course of hundreds of 1-5 minute lecture videos. I took thorough notes and spent and average of 3-5 hours on each module. Good The amount of knowledge you will take away from this course. I didnt know a lot about computers in general before this course, so I went off on some learning tangents in the middle of the videos. Overall I feel like I have a much better base than before. Slack was awesome to work through problems with other students and get help, but I did not like Piazza as I hate their UI and found it very hard to use and find what I needed. TAs were really helpful and their attitude in answering questions was proportional to the intelligence of the question. Despite all the hidden stuff lots of people including me complains about (see below), I thought the projects were really well put together and were super captivating. Bad In project 1 a little, and project 4, it did feel like we were herded to implement the solution in a specific way. It did take a lot of extra time to figure out the abstracted functions / files in project 1, and in project 4 it felt limiting only being able to edit and submit certain files. However, after spending some time with the code it becomes clear why it is structured this way and in the end I dont have any major qualms with it. The exams are weighted too heavily in my opinion. A project takes ~50 hours and is worth 15%, where exams are 25%. Some exam questions test your memory on little details, so if you lose 5 or 10 points on one of them, it is almost equivalent to 5 hours of project time. I get that the concepts are important and we should know them thoroughly but I would be more happy with the exams and projects being equal, especially since the projects are so grueling and time-intensive. There probably wouldnt need to be such a large curve this way. There are a bunch of errors in the quizzes and some lecture videos, I would have expected them to re-make the videos at some point in the past 10 years instead of leaving errata notes below which are very easy to miss. Rating: 5 / 5Difficulty: 3 / 5Workload: 17 hours / week - ymZc+tY36sXteFxpQeZ28Q== December 30, 2025 fall 2025 [Distributed Computing](https://www.omscentral.com/courses/distributed-computing/reviews) I took this course in Fall 2025, and it covered topics I’m genuinely passionate about in distributed systems. I finished the course with an A (88%). Overview The course starts relatively slowly with lectures, followed by Project 0 (intro), Project 1 (client–server), and Project 2 (primary–backup replication). The lecture material is good, and both the required and optional research papers are excellent (long term). Many are still highly relevant in industry today (saved and reading them now after the course :) ). Working knowledge of Java is needed to do well IMO as a good amount of coding/debugging is needed. The real challenge begins with Project 3 (Paxos) and Project 4 (KV Store). IMO, Paxos is the harder of the two. I worked on the projects almost every day, and while demanding, the experience was rewarding. Running tests locally (macos) helps with time and quicker iteration. That said, there are some notable downsides: The DSLabs framework has a steep learning curve. Even by the end of the course, I didn’t feel I fully understood all of its internal workings. Some tests are extremely strict, especially with tight timeouts and DSLabs-specific requirements (e.g., running with --checks for idempotency, checking correct equals() / hashCode() behavior for search tests, etc.). It’s worth noting that passing all tests is not required, and the grading curve helps significantly. Pros A wealth of high-quality material, especially valuable if you already have experience building software components from the ground up. Project4 reference implementation helps and didn't find it confusing. Well-structured lectures with a great selection of research papers. Exams are easier than AOS, fully objective and with sufficient time. The trade-off: each question carries more weight, so mistakes are costlier. Cons The test framework for Projects 3 and 4 is rigorous. Must start early and invest time understanding readme.md and DSLabs framework. Final Thoughts Overall, this is a strong and rewarding course for students interested in distributed systems, especially those who enjoy both theory and hands-on implementation. If you’re willing to commit time consistently and don’t get discouraged by test failures, you’ll learn a lot. That said, I think the course could benefit from leaning more clearly toward either learning (theory) or implementation, rather than straddling both as heavily as it currently does. Rating: 4 / 5Difficulty: 4 / 5Workload: 35 hours / week - uGdPLFYuNjNE0R+60hFMKg== December 30, 2025 fall 2025 [Statistical Modeling and Regression Analysis](https://www.omscentral.com/courses/statistical-modeling-and-regression-analysis/reviews) This class is overbloated garbage. Everything feels like a chore. They shoved 2 midterms, both coding and mc into it and the instructions for the coding portion is a multistep mess. There's a crappy group project but you cannot even pick a topic you want to do. The least offensive portion of the course is the homework, but even that is overly long. Some of the TAs are also very condescending and feel the need to add extra bs to their responses to student's questions. Just take another elective over this trash class. Rating: 1 / 5Difficulty: 3 / 5Workload: 10 hours / week - toohORXUybDr8ej6qtCbDA== December 30, 2025 fall 2025 [Introduction to Information Security](https://www.omscentral.com/courses/introduction-to-information-security/reviews) This course felt more like a bunch of mini-courses, with most modules having a different set of TAs. It's entirely CTF based now. Most projects had flags that you'd submit, and the tasks that required code submissions ran it through an autograder. There's no subjective grading: you know your grade after each submission. There were some assignments with submission limits, but they were lenient and I never felt much pressure. This course will tear you up if you don't have a decent coding background. I took two years of Python in undergrad and still had to take some time brushing up on things. Some modules were better than others. MITM was easy and made for a good warmup. Malware analysis consisted almost entirely of reading reports and was kind of a letdown. Binary exploitation was tough for a lot of us (including me) but it was very informative. Extra credit was available on some assignments. You can't depend on it being there, but they do offer it at least sometimes. I'd say about 3 extra points in total were available on your final grade if you went for all of it. The professor was entirely absent. Not an announcement post, not a lecture video, nothing. The class was entirely run by TAs, at least from my perspective. That said, the TAs were helpful and the discussion boards will be your friend. You'll need to know how to do outside research (follow the syllabus) if something isn't familiar to you. The workload varies a lot. MITM took me ~10 hours or less, whereas binary exploitation probably took me at least 40. VM setup worked just fine on my Windows laptop. You'll want to know basic Linux commands (how to navigate the filesystem and run scripts, for example). I'd suggest doing some practice on HTB Academy (\$8 a month with your student email) and/or picoCTF (free). There's other resources out there as well, like DVWA if you want to practice Database Security before you start the course. Overall, it was difficult but not unbearable. I got an A while working full time. I passed the OSCP in 2024 which helped a bit but there was still a lot of learning I had to do. Rating: 3 / 5Difficulty: 3 / 5Workload: 25 hours / week - tQDYQZAdQEOyu+fkV4eVtw== December 29, 2025 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) TLDR: While I finished the course with a high A, I had mixed feelings about this class. In particular, I felt like there was a significant imbalance between the course's workload (somewhat high) and the actual depth and difficulty of the work (pretty low), which I feel led to me disengaging somewhat with the material; I found myself wishing topics were explored in much more depth. I did not feel like the team project actually was able to dive deep enough into the design process to justify its existence. This course is pretty evenly divided into thirds. For the first 1/3rd of the course (the "Content" phase), you are watching the entirety of the class's lecture content, along with completing a weekly homework assignment (Homeworks are 4x5% = 20% final grade). The course content is divided into two major units, Principles (essentially the theories behind interface design) and Methods (the design lifecycle, how to prototype and evaluate an interface). The lectures are excellent, Dr. Joyner is an exceptional presenter and brings very good energy to the videos, they are very easy watches and convey the necessary information very well. I found the actual content behind the "Principles" unit to be much more interesting than the "Methods" unit, which often felt a bit surface-level (I'm a grad student, I know what different types of data are and how to use statistical tests), but the course endeavors to be entry-level, so whatever. The homeworks each consisted of answering 4 questions in 8 or fewer pages. Like many things in this course, it felt like these were graded quite easily and straightforwardly. The second third of the course (the "Practice" phase) felt like it ramped up the workload quite a bit. This phase consisted of reading the associated texts with the course, completing four quizes (4x5% = 20% final grade), along with working on the individual project (15% final grade), and taking 1 out of the 2 course tests (10% final grade). The readings varied in quality considerably. Many of them felt like "slightly-reworded-lecture-content-but-worse", but a few of them were interesting. The quizzes felt very fair. Studying the lecture content felt straightforward (like I said, the lectures were good). One question on each quiz was from the assigned reading, and the instructor informed us ahead of time which reading would be on the quiz (I dunno about this one, this feels maybe a little *too* nice). The project consisted of selecting a design task, performing needfinding for that task (for 95% of people, this meant posting a survey for the class), designing three prototypes, evaluating these prototypes (for 95% of people, this meant posting a survey for the class), making a higher-fidelity final prototype, and having people evaluate it (for 95% of people, this meant posting a survey for the class). I didn't really mind the project, although it appeared to be a massive procrastination trap for a lot of people. It did sometimes feel like a lot of the survey responses were low-effort (we got participation points for completing surveys). Writing the project report (max 25 pages) felt like the same straightforward grading as the homeworks; if you do everything the assignment asks, you can expect a 100, no surprises. The final third of the course (the "Application" phase), consisted of a team project (15% final grade), along with taking the remaining test (10% final grade). If that sounds a lot easier than the last phase... yep. The tests were open-note, open-internet. They felt like the kinda assignment where its extremely easy to get an 85%, easy to get a 90%, and quite difficult to get a 100% on (which, coincidentally, is the opposite of the rest of the course). I don't have much more to say about them. The team project was nearly an exact reboot of the individual project; the major differences were an increased page limit on the report (max 40 pages), and the vague direction that our prototypes should be higher fidelity. I didn't like this. It didn't really feel like we had a chance to dive deeper into the design process, since (as mentioned), I felt like poor survey responses were kinda bottlenecking the interface design anyway (the instructor plans to require interviews for the team project feedback in the future, which I do think is a good idea). In addition, there is also the classic team-project roulette; my team had one person completely unresponsive, and another who had to be prodded quite a bit to do work. I think these kinds of projects are fundamentally unfair, end of story. The remaining 10% of the grade comes from course participation, for most people, this meant spamming low-quality survey responses. I wish there was a better way to align incentives to encourage thoughtful responses, but I can't really think of anything. Dr. Joyner intended this course to take ~10 hours per week. I think it mostly does, with the caveat that unless you're willing to work a bit ahead, you will definitely have weeks that exceed that, and that the final third of the course is much easier than the other two. I'd probably scooch a quiz or two into this final phase if I were running the show, but it's not a huge deal. I would advise anyone taking this course to heed the instructor's advice about proactively forming your own team instead of doing the matchmaking survey (to increase your odds of avoiding slackers), and to be proactive with the project work. But the class is very straightforward (potentially to a fault) if you don't mind things being somewhat introductory, and having a moderately bumpy workload. Rating: 3 / 5Difficulty: 3 / 5Workload: 10 hours / week - Leq5tv8IK8tghRyJLzn6eA== December 27, 2025 fall 2025 [Special Topics: Applied Natural Language Processing](https://www.omscentral.com/courses/special-topics-applied-natural-language-processing/reviews) This was by far the worst course I took on the programme. Don't expect to learn much from the classes (as they have nothing but a teacher reading the slides without taking note of anything) - most of the things I learned came from putting the class transcripts into ChatGPT to get explanations. The assignments are disappointing as well… they were useful in a certain way because I had to learn how to work locally using .py files (in a "object-oriented way"), but I found them pretty easy (as much of the code is provided). Overall, I learnt some stuff (and the course content is pretty up to date), but it wasn't worth my time or money. Rating: 2 / 5Difficulty: 2 / 5Workload: 7 hours / week - BbZ3VI+UXIBBvTaYgCBzpw== December 24, 2025 summer 2025 [Introduction to Cyber-Physical Systems Security](https://www.omscentral.com/courses/introduction-to-cyber-physical-systems-security/reviews) This is for Fall 2025. I really enjoyed CS-6263 and found the projects fun…but that could be due to my background in logic and circuit design. I echo the same advice others have given — start the projects early. Project 1 took about 25 hours total and consisted of a part A and B. Part A only took about 5 hours, including reading up on how to use the tool and watching tutorials. Part B was more challenging but in a fun way — I actually completed it in 15 hours but spent another 5 hours fine-tuning things. Project 2 took about 15 hours. Ladder Logic is a breeze if you’re familiar with logic gates and parallel signal propagation. If not, then it could take 2-3x longer to finish the project while you brush up on related concepts. Project 3 was different from past semesters and only took about 5 hours to practice sniffing for ICS devices. Project 4 gave brief exposure to machine learning. It seemed daunting at first but turned out easier than I expected. It helps if you’re familiar with Python or object-oriented programming. You are provided with a working skeleton model and have to fill in additional portions of code to make the project functional. Once you get your ML model to run properly, then you further refine and optimize your machine learning algorithm to hit the grading targets for accuracy and relevancy. I was a little worried at the beginning of the semester after reading some of the other reviews because the difficulty level can be deceiving. Fortunately, my background in computer engineering served as a great foundation for all four projects and I finished each project with anywhere from 5-9 days to spare (primarily because I started projects early). I actually struggled more with the exams. It is true, the lectures are completely independent of the projects. I didn’t mind this as I could focus more on the projects early on and come back to the lecture material later when it came closer to the midterm/final. You are allowed one page single-sided notes for the midterm and one page double-sided for the final. The lectures are all done well, some of the best production values I’ve seen in OMSCS so far, and I found the material all very interesting. Still, I was thrown off by the wording of some exam questions and received a C on the midterm and a B on the final. I still finished with an A overall in the course by averaging 98% across all projects. There is also a 20-minute video presentation you have to do based on a research article. It is an easy 100 points. You get to select your presentation date and I quickly picked the latest available week for due dates. I suggest you do the same so the presentation doesn’t interfere with your first or second project. By the time you’re on project 3 and 4, the pace of the course really slows down and you’re in a lull in the semester so it’s a perfect period to then focus on your presentation. I recommend this class for any of the OMS specializations, either as a requirement or elective, because the course is interesting, the projects are neat and fun, and the difficulty level/time commitment is very manageable for balancing family and career. One last remark, I have to give credit to the amazing TA support team. The TAs ran Ed Discussion superbly and were responsive and gave helpful advice. Office hours were also extremely helpful. I was kind of shocked at how few people attend office hours; sometimes it was just me and the TA one-on-one (which was great for getting personalized help). Maybe everybody else knew what they were doing and didn’t need the help but I was grateful for how accessible the TAs were. Whenever I was in a quandary, or found the project instructions unclear, it was quick and easy to get clarity in office hours or through the discussion board. Rating: 5 / 5Difficulty: 3 / 5Workload: 10 hours / week - cvUKRHrSDa+Z2dn5TUe48Q== December 24, 2025 fall 2025 [Database System Implementation](https://www.omscentral.com/courses/database-system-implementation/reviews) Medium-effort, high ROI course. 4 Assignments 3 quizzes 2 exams Great class if you are interested in understanding how databases are built from scratch. The assignments focus on implementing a beta version of BuzzDB in C++ and iteratively improving it over the course of the assignments. One of the nicer things is that there are no hidden test-cases. Passing the test-cases locally almost always guarantees a 100% on gradescope. B+ tree (assignment 3) was the most challenging one. Quizzes: These are proctored quizzes (via honorlock) that mainly focus on the lectures. Combined make up around 25% of the grade. They aren't too bad , but there are 3-5 questions that can seem from material not included in the lectures but need general database knowledge to answer Exams: Same as the quizzes but with the material from the papers, especially the final was mostly from material in the papers. But the professor mentions the important sections from the papers relevant to the exam. My advice would be to focus on those. Curve 85% was an A , it looks like the course is getting tougher with time. % of As has decreased compared to previous semesters. One of my criticisms is the weightage of assignments relative to quizzes, quizzes seem like beta exams, and sometimes I felt that they weren't really needed . Instead they could add up-to 2 extra assignments dealing with in-depth concepts from databases. This is where the course missed the bar slightly. Overall , a great course, put in the effort and you will be fine. The professor and TAs genuinely care and want the students to succeed. My grade A - (89%) Rating: 5 / 5Difficulty: 3 / 5Workload: 14 hours / week - 2c1btKEcjhtxtHHB8f2rMg== December 24, 2025 fall 2025 [Knowledge-Based AI](https://www.omscentral.com/courses/knowledge-based-ai/reviews) Background: 1st semester student, Undergrad CS major, working as a Data Scientist for less than a year. Finished the course a month early and ended up with an A(91.89%). Pros: - The lectures are very interesting and enjoyable, and they are presented in a way that’s easy to understand. - The coding assignments aren’t too difficult and are manageable. - The TA and Dr. Joyner are great and respond quickly when help is needed. - The integration with gradescope is cool, you are able to submit coding assignments up to 40 times and it auto grades so you can see your grade right away. Cons: - The lectures don’t align very closely with the assignments; the assignments aren’t really AI focused and feel more like general coding tasks. - The writing assignments feel somewhat useless and repetitive more like busywork that could be avoided. - I received feedback on early assignments, but later in the course I didn’t get any feedback at all. Homework(15% )- 90/100: These are writing assignments (journals) based primarily on lecture material. Make sure to follow the prompt questions closely and answer them clearly and completely. Demonstrate a strong understanding of the relevant lecture concepts and apply them accurately. When a prompt asks for a diagram, ensure that it matches the one shown in the lecture exactly. In a previous assignment, I mixed up two concepts and received no credit for either, which resulted in a C on that assignment so accuracy is very important. Exams: Midterm(7.5%) - 70.91/100, Final(7.5%) - 92.72/100: I’m not a great test taker, so I didn’t do very well on the exams. They aren’t too hard since they are open notes and open internet including AI, but you still need to understand the concepts really well. On the first exam I struggled with time management and ended up turning to ChatGPT as a last resort, which didn’t help much. After that poor result, I made really good notes and used NotebookLM by Google to ask questions based on them for the second exam, and I ended up doing much better. I recommend that if you are unsure if a statement is correct to leave it unselected. Mini Projects: Performance(15%) - 98.5/100, Journals(15%) - 95.4/100: The coding assignments are fairly easy and similar to medium-level LeetCode problems, so they shouldn’t take too long, except for Mini-Project 2 (Block World), which was difficult and cost me a few points. Overall, the assignments are manageable. The writing assignments are short (max 4 pages), but I lost points for not including metrics related to efficiency and performance. ARC-AGI project: Performance(7.5%) - 100/100, Journals(7.5%) - 100/100: For the assignments, you’ll be solving ARC-AGI problems by creating an agent. I didn’t implement any real AI methods myself, what I did was design a specific solution approach for each problem. To achieve full credit on each milestone, you need to pass at least 6 out of 16 general test cases and 6 out of 16 hidden test cases. The journals can be repetitive, so feel free to reuse the same structure each time. Just make sure you include specific metrics for each milestone, including: Efficiency: Big-O complexity and actual runtime, Performance: Number of test cases passed Keep in mind that even though you only need 6/16 for both general and hidden tests at each milestone, you’ll eventually need to solve all of them for the final project. Because of that, I recommend completing as many problems as possible throughout the milestones rather than waiting until the end. Final ARC-AGI project: Performance(7.5%) - 84.38/100, Journals(7.5%) - 76/100: Each milestone (Milestones B through D) includes 16 general tests and 16 hidden tests, for a total of 48 general tests and 48 hidden tests across all milestones. I wasn’t able to solve 15 of the hidden tests, which left me with a performance score of 81/96. My performance wasn’t as strong as it could’ve been because I decided it wasn’t worthwhile to spend hours trying to figure out each hidden test for just a 1 point increase. The final journal grading is much stricter than the other journals. I answered every question on the assignment, but some parts were considered vague by the TAs, which lowered my score. I put in the same level of effort as I did for every milestone, where I earned 100 out of 100, but the TAs expected more for the final journal. I recommend being very clear and keeping in mind that the grading is stricter. Participation(10%) - 100 / 100: These points are basically free, and there are plenty of opportunities to earn them. I mainly completed peer reviews each week to stay ahead. After about two months, I had already earned the full 90/90 points and didn’t have to think about it for the rest of the semester. Rating: 4 / 5Difficulty: 3 / 5Workload: 12 hours / week - UxM4W8UQJZ4uBeXkBIQvBQ== December 23, 2025 fall 2025 [Introduction to Graduate Algorithms](https://www.omscentral.com/courses/introduction-to-graduate-algorithms/reviews) This was my least favorite course so far although I do understand the importance. Many of the algorithms are not practical but help establish a mindset on how to simplify. Students will learn how to assess the time complexity of an algorithm, some common approaches to simplifying and solving problems and how to deal with problems that may not have clear solutions. This I liked. I also liked the lectures, although they were all recycled from a former instructor. The homework assignments are graded but have zero weight on the final grade. Exams have the heaviest weight. The multiple choice problems are tricky and the grading is subjective and probably dependent on who graded your work and how they were feeling when they did it. It was hard to review exam results. You are not given direct feedback on multiple choice questions and for the proofs the feedback is obscure. I didn’t really care to try to interpret it once I had a B. There is minimal coding in the course. Most of the coursework involves solving problems in words, similar to writing proofs. There is a textbook for the course, Algorithms by Dasgupta. This and the recorded lectures are assigned in a disjointed order throughout the course, which disrupts the flow. The textbook is also concise and often requires the reader to fill in some ideas themselves, which required me to do a lot of rereading In conclusion, I found that the course useful, I mostly disliked the work (quizzes, exams and homework), the grading was harsh and subjective and the textbook was difficult to follow. Rating: 3 / 5Difficulty: 4 / 5Workload: 8 hours / week - 4v+GPNibbZHV4cDoKVlvvg== December 23, 2025 fall 2025 [Video Game Design and Programming](https://www.omscentral.com/courses/video-game-design-and-programming/reviews) As others have said, watch the lectures at 1.5-2x speed. The content in them is good though, there's a lot of really interesting stuff. Unfortunately I do think a lot of references that he makes will be lost on folks who aren't into gaming. There's a LOT of "history of gaming" style stuff, which makes sense when studying game design, but is much easier to grasp if you are into gaming and so have some context as to who Valve or id Software are. The project is what you make of it, but is easily the biggest time sink in the course. Coordinating with teammates is hard in Unity (merge conflicts are basically unsolvable, so you have to work on different things), so a lot of cognitive overhead comes from just that aspect of the project. As for actually learning Unity, yeah, you could just do it yourself - but Dr. Wilson gives some assignments that help introduce you to the engine, which can be intimidating. And I really do believe there's some value in working on a game with other people in a team to see how they do things, even if there is a lot of overhead in the coordination. Also, being forced to go through the process of making a game from start to finish, with all of the steps in between (alpha, playtesting, etc) is really a good exercise in forcing you to do steps you might want to ignore if you're just playing around on your own. All in all, not a hard class, but you can really go wild with the project if you want, which could end up taking a lot of time. Take this class if you want a semi-structured excuse to play around with Unity for several weeks/months, and if you want some interesting discussion of game design philosophy. Rating: 5 / 5Difficulty: 3 / 5Workload: 20 hours / week - Flq5Ybni4B0gY/9Ddy8jjQ== December 23, 2025 fall 2025 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) This is my first OMSCS course and I feel I learned quite a bit. I did not formally study Computer Science in my undergrad so everything over here was pretty much new to me or things I didn't know in a lot of detail. I really enjoyed the projects and I feel that was where I learned the most. The mid term was relatively easy but that could also be because the first two modules are easier than the last two. The effort I put into the course was quite sporadic, to be honest. I mostly spent the weekend before project deadlines working on the project. This is not how I like to do things but I just joined a new team at work and there was a lot going on so unfortunately this was the case. I would recommend getting headstart on the projects because there were really times when I was so stressed and worried that I wouldn't be able to complete the project but I was lucky and did well on the projects. The end term was the hardest for me and I barely got 48 hours to prep for it but that was because of my personal circumstances. However, because I did well on mid term and the projects I still managed to get an A. Overall, I feel if you keep up with the schedule they recommend, you can comfortably do the course. You get plenty of time between projects as well. The exams are MCQ and fill in the blank style but similar to the quizzes in the lecture. The end term is relatively harder and I would recommend allocating good chunk of time for that. The professor and TAs were all very nice and gave pretty good feedback as well. Rating: 4 / 5Difficulty: 2 / 5Workload: 5 hours / week - lVaErvC+H+S2COrzPeOalw== December 23, 2025 fall 2025 [Introduction to Health Informatics](https://www.omscentral.com/courses/introduction-to-health-informatics/reviews) Finished the course with an A, achieving a 102.88 % Background: Bachelor's degree in Computer Science from a university ranked \#350-400 out of 436 National Universities in U.S. News English is my second language (TOEFL score: 95/120) 1 year of experience as a full-stack developer and 6 months of experience in data analytics Overall: This class is fairly easy, especially if you have experience with full-stack development or have built applications before. If you’re interested in working in the healthcare industry, this course provides an entry-level introduction to using REST APIs and interacting with a testing server. You can be as creative as you want with the project and even try out new tech stacks you’ve never used before. As long as you put in reasonable effort and build something enjoyable, getting a good grade is very achievable. Labs (39.07 / 35%): There are six labs plus two extra credit labs, and as long as you follow the instructions, you should get full credit. Some students on the forum complained that the setup instructions didn’t work in their environment. If you’re going to graduate from OMSCS, you should understand that no single setup works perfectly for everyone. Read the error messages and debug your environment yourself. Quizzes (19.31 / 20%): The quiz questions mainly test whether you watched the lectures. They’re pretty challenging, but you get two attempts, so overall it’s fair. I’m a horrible test taker(Check Digital Marketing Review). Practicum Project (34.5/ 35%): You can form your own group, and finding teammates who match your working style is ideal. It’s pretty easy to earn a high score, and the workload can feel either very light or very heavy depending on your group dynamics. Overall, the points are easy to earn. Other (6 / 6%): These are survey points—easy to earn. Participation (5 / 5%): These points are also easy. Try to complete them early so you don’t have to worry about them later in the semester. Rating: 4 / 5Difficulty: 1 / 5Workload: 6 hours / week - lVaErvC+H+S2COrzPeOalw== December 23, 2025 fall 2025 [Digital Marketing](https://www.omscentral.com/courses/digital-marketing/reviews) Finished the course with an B, achieving a 83.71 % Background: Bachelor's degree in Computer Science from a university ranked \#350-400 out of 436 National Universities in U.S. News English is my second language (TOEFL score: 95/120) 1 year of experience as a full-stack developer and 6 months of experience in data analytics Overall: This is probably the only B I got in the OMSCS program. I got As in my other courses like GA, ML, AI, KBAI, etc. I took this class because I felt a bit burned-out and wanted an easier semester, but it turned out harder than I thought based on my background. The biggest challenge was the exams because they focused too much on remembering English words and terms. Since English is not my first language, the questions were long and hard to understand sometimes, even though I studied. Still, I don’t regret taking this class. It was well organized and helped me learn how people use computers and mobile devices. As a data analyst who builds machine learning models for medical systems, this class gave me good ideas about how to collect and use user data. Major-Case Reflection Assignments (20 / 20%): These assignments are interesting, and as long as you understand what the question is asking and answer it correctly, it shouldn’t be a problem to get 100s. Weekly Mini-Case Discussions (20 / 20%): Smaller than Major-Case, you only need to watch the lecture video and explain what you think about the question. It’s fun and helps you learn some real historical cases. Midterm Exam & Final Exam (22.28 + 21.43 / 60%): The weight for this is just too high, as the overall summary explains. I tried my best. Rating: 5 / 5Difficulty: 2 / 5Workload: 6 hours / week - FC25WM4yyLYkJyZFjWz6mg== December 22, 2025 fall 2025 [Data and Visual Analytics](https://www.omscentral.com/courses/data-and-visual-analytics/reviews) I’m genuinely surprised this a required course for the OMSA program. If Georgia Tech prides themselves on providing leading education, this course is certainly not living up to that standard. The content feels like a hodgepodge of loosely connected material, nominally centered on visualization, but without much depth or cohesion. The lectures are extremely broad and don’t align well with the assignments. The workload is lighter than in most other OMSA courses. The D3 assignment in Homework 2 is the only part that takes a bit longer. D3 is tedious to learn and I highly recommend completing D3.js Essential Training by Emma Sanders on LinkedIn Learning. It will significantly help in completing the assignments. Half of the course grade is based on a group project with at least five team members. I generally dislike group projects with people I don’t know, but ironically, this ended up being the most enjoyable part of the class. Advice for Taking This Course: - Take it later in your program. You’ll be better equipped to define a meaningful project once you have more context from other OMSA or OMSCS classes. - Form a mixed group. A team with both OMSA and OMSCS students will bring strengths from the analytical and the computer science areas. - Choose a manageable project. Pick something with a clearly defined goal and a dataset that can be obtained. Start with a simple idea - you can always add complexity later. - Find your group early. Be proactive. Try forming your group at the very start of the course (or even just before it begins). - Meet weekly and stay organized. Set an agenda, assign roles and tasks, and ensure at least one team member keeps the project on track. - Check the checklists! The course, and especially the project, is full of detailed “to-do” lists that can make you feel micro-managed to the n-th degree! If you want a good grade, be sure to complete every item on those lists. Rating: 1 / 5Difficulty: 2 / 5Workload: 10 hours / week - /Uu79+lLvUsTQmFQj8joqA== December 22, 2025 fall 2025 [Applied Cryptography](https://www.omscentral.com/courses/applied-cryptography/reviews) ## My Impressions of the Course This was my first course in OMSCS. I made a decent A. This review may be a slight outlier because my academic background influenced how I approached this course (I have a master's degree in mathematics). If you don't have a mathematics background, it can be a bit difficult to adjust to how this course flows, because it's essentially a mathematics course in the formalism. ### Good Points - The TAs were very helpful and prompt to answer questions. - I even got answers to questions outside of the scope of the course (for instance, a proof regarding the DES complement property). - The material was presented in a very understandable way with a references given in the weekly Ed posts for reading from the recommended texts. - The homework assignments were very interesting, for the most part (coding homework 2 being the outlier; I'll touch on that later). - Coding Homework 1, in particular, was a very nice balance of being possible to break without requiring too much knowledge to break. - The quizzes were a bit on the easy side, but at least kept me engaged and accountable to some sort of routine. - The exams were just the right level of difficulty, where the points I lost I could entirely blame on myself. ### Neutral Points - There was no discussion on the designs of any of the cryptographic primitives or schemes presented. - I understand that this course isn't about implementation and all of the associated quirks (like constant-time operations to avoid side-channel attacks, which are meddled with by compiler optimizations), but at least having an idea of what the tools *do* would have been interesting. - I would have been okay with references to the standards / specifications. - While readings were given from the texts for the material, I would have liked if there were more readings from the literature to go into deeper detail or to see additional aspects that might not have been considered. - "Communication Theory of Secrecy Systems" by Shannon, "New Directions in Cryptography" by Diffie and Hellman, "A Method for Obtaining Digital Signatures and Public-Key Cryptosystems" by Rivest, Shamir, and Adleman, and many more papers are absolutely foundational and should be known by anyone in cryptography. - And papers like "Mining Ps and Qs: Detecting Weak Keys in Network Devices" by Heninger, Durumeric, Wustrow, and Halderman are important for understanding that weaknesses aren't just about the schemes and models, but about how they're implemented and used. - There were a couple of lectures about scheme implementation issues, so I won't say that this concept was completely ignored. - Again, however, more references means more opportunities to learn\! ### Bad Points - If I had to nitpick, I think the worst part of the course was how slow the lectures felt. - However, this was easily dealt with by watching at 1.5x speed. - Another issue is that I wish it was easier to download the videos for offline viewing. - I had to use the developer console to monitor for .m3u8 and .mp4 files and use FFmpeg to download the .m3u8 files to .mp4. - Some videos were .m3u8, others .mp4, so I couldn't just search for .m3u8 or just .mp4. - FFmpeg command used: `ffmpeg -protocol_whitelist file,http,https,tcp,tls,crypto -i video.m3u8 -c copy -bsf:a aac_adtstoasc video.mp4` (here, video.m3u8 is whatever you saved it as) - Since each lecture was broken up into 15-20 3-10-minute videos, this was quite tedious. - Coding Homework 2 was a bit too trivial. - Unfortunately, this comes with the territory. - Anything "breakable" is either trivially so or requires more knowledge than this course can give in a single semester from the level that students are expected to enter at. - The one exception I can think of was Coding Homework 1's problem. - Instead of requiring students to break a scheme, giving students a chance to build something might be a good alternative. - Maybe using this as an opportunity to walk students through how to implement a secure scheme using publicly available Python 3 libraries would be better, since it's a *very* small portion of a student's final grade. ## General Tips/Information - You'll want to be comfortable with reading and writing proofs, analyzing *what* a statement and proof are telling you mathematically, and have a decent grasp of discrete mathematics (elementary number theory, basic combinatorics, discrete probability). - If you have time before starting the semester, check out [MIT 6.042J (Math for Computer Science)](https://ocw.mit.edu/courses/6-042j-mathematics-for-computer-science-fall-2010/). - This has basically all of the mathematics you'll need. - Pay close attention to definitions. Remember them, internalize them. - This means taking the time to understand both the formal and conceptual meanings. - Use the proofs in the videos as templates for how you should write your solutions in the written homework and exam problems. - I highly recommend that you learn LaTeX so you can typeset notes and solutions. - Exams will require typing your solutions in some way, so being able to render your solutions to PDF using LaTeX will be helpful for readability. - You'll want to have a local installation for rendering your LaTeX to PDF, because Overleaf (or any other web-based editor) are not allowed during exams. - I used VS Code with texlive in WSL2 on Windows 11 and it worked just fine. - The lowest written homework grade and lowest quiz grade are dropped at the end. - Note that coding homework and exam grades are *not* dropped. - The grades are weighed as follows: - Quizzes: 15% - Written Homework: 15% - Coding Homework: 5% - Midterm: 30% - Final: 35% - There is a curve applied at the end, but the default grade intervals given in the syllabus are: - 80% \< Grade \<= 100% is A - 60% \< Grade \<= 80% is B. - So on for each 20% interval below. ## Homework Tips/Information - Most of the homework problems were about breaking a proposed scheme or (rarer) building a secure scheme using cryptographic primitives. - For the problems that ask you to build a secure scheme, you're not generally expected to prove that they're secure from base principles. - Instead, you just cite the relevant results from the lectures. - Make sure to pay attention to the resources your attacks use. - For written homework, make sure to use Gradescope's labeling feature to label which pages correspond to which problems. - You'll lose points if you don't mark the pages\! - Written homeworks are assigned every other week with one-week deadlines; there are a total of two coding homeworks, each with two-week deadlines. - The coding homeworks used Python 3 and were actually very easy. - The first coding homework took about an hour of coding and writing the report, but I had the advantage of having implemented the cryptographic tool used in the problem in C++ prior to taking the course. - A couple of hours of sitting with the RFC and realizing there's only a small part of the specification that's actually the crux of the weakness of the scheme should be enough to figure it out. - The second coding homework was absolutely trivial. It took about 15 minutes, and that includes running the code. - My overall homework grades: ~99% for written, 100% for coding. ## Quiz Tips/Information - The quizzes are very short and easy. - The answers are either verbatim lines from the videos / slides or can be easily deduced in one step. - You do need to pay attention to the questions. - If you're like me, you may misread a question and answer it incorrectly as a result. - For the first half of the course (through the midterm), quizzes test material from the previous week. - For the second half of the course (after the midterm), quizzes test material from *that* week. - Don't let the switch up catch you off guard. - I think this should have been better communicated (or should have remained consistent). - My overall quiz grade: ~97%. ## Exam Tips/Information - All exams are open notes but closed internet (besides a few links they whitelist). - I suggest having everything they allow you to use downloaded and ready to go on your computer (slides, the main texts, and external notes they may provide), even though they whitelist the links. - I felt much more comfortable knowing that I wouldn't have to open extra tabs in my browser and wait for them to load. - Use the quizzes as study material for the multiple choice portions of the exams, and use the written homework as study material for the written portions. - The multiple choice questions felt like they could have been alternative quiz problems. - The written portion of the exams tended to require a bit less insight than the written homework problems in the sense that it was much easier to see what you needed to do to solve them. - Don't rush, there's more than enough time (2 hour time limit). - Most of the points I lost in this class were on the exams because I didn't use the time as wisely as I should have. - My main issue was writing my general idea of an attack but forgetting to return to the problem to fill in the details after moving on. - Don't make this mistake; reread your solutions thoroughly before submitting. - Just like with written homework, you have to label which pages correspond to which written problem from the exam when uploading to Gradescope. - My exam grades: ~92% for midterm, ~86% for final. **My overall grade:** - 92% (raw score from the grade calculator provided by the staff) - A (letter grade) Rating: 5 / 5Difficulty: 2 / 5Workload: 7 hours / week - y95bmX+tFh3XCTGPOgZ78A== December 22, 2025 fall 2025 [Reinforcement Learning and Decision Making](https://www.omscentral.com/courses/reinforcement-learning-and-decision-making/reviews) RL is my 6th course at GT (AI/AI4R/ML/CV/RL). I got an A. I felt as though the course had the following issues: - The readings are pulled from a free online book and quite long, covering several topics that aren't pertinent to the projects. Likewise the required lectures are not useful for the projects beyond week 2-3; most students recommend watching a different set of lectures (David Silver). Personally, I didn't find the supplemental lectures or office hours useful. I ended up skipping the readings and lectures after the first few weeks. - The environments take a long time to run (e.g. \>3 hours); this means you have relatively few attempts to modify hyper-parameters which is challenging because there can be 1-2 dozen parameters to tinker with (and there is no working set of parameters supplied). - There is little to no 'hands-on' explanatory material. For example, there is little to no guidance on what kinds of diagnostics to use when trying to find a working set of hyper-parameters, and no discussion of how to interpret the results of those diagnostic measures. A short (time-lapsed) example where the presenter walks through finding a working set of hyper-parameters by examining some set of diagnostics on a problem they aren't already familiar with would have been informative. - As with ML & DL, the feedback comes late (6-8 weeks into the program), is infrequent (4-5 week periods), last-minute (prior report's feedback arrives 1-2 days before the deadline of the next project), and is often very brief, e.g. ~30-50 words per 8-page report (RL). I have never lost points for being incorrect (although I likely am), but only for omitting required material. The requirements documents are lengthy (\>7 pages) and the (graded) requirements are not always condensed into the 'requirements' section. - The final environment is not well-constructed; it's a 90s-looking game that runs at 10 FPS on modern hardware, and only on Intel CPUs. If you have a non-intel processor you will need to rent a computer. The school's PACE cluster may be available, but seeing as the project's assigned at the end of the semester (and around Thanksgiving in the fall), you'll likely be competing heavily with other students for access. - The final (MCMA) had little to do with the projects which dominated the time I spent on this course. I got a little above average, which was a bit below 50%. If you're dying to do well, review the (later) lectures and skip the textbook. I know more about RL after taking the course, but apart from the credential your time may be better spent doing personal research; the David Silver lectures are free, as is the Sutton & Barto textbook. I liked the OpenAI 'Spinning Up' explanations (e.g. for Proximal Policy Optimization \[PPO\]). Rating: 1 / 5Difficulty: 4 / 5Workload: 24 hours / week - Jlk0Gmfu1LnHpUt+1kQVyQ== December 22, 2025 fall 2025 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) Background: I graduated in Fall 2024 with a BS in CS at a similarly ranked school. I took Operating Systems there but had to drop the course. This is my first OMSCS course and I am currently work in Devops/Infra. This is the only course I took this semester. I got an A in the course. Overall, this was a great course, and a great introduction to OMSCS. The lecture content was interesting and presented in an easy-to-understand method. The lectures were split into 20 or so short videos and some quizzes to accompany them. This made it easy to rewatch parts of the lecture content I had trouble understanding, as I just needed to find the accompanying video. The material itself was not too difficult to understand, however my background definitely helped me in this regard. The readings were also interesting, and lecture content goes over their important concepts in good detail. The projects were the real fun portion of the course. I enjoyed every project and learned a great deal from each. They are not OS-specific projects, but deal with network programming, and helped me understand some of the concepts we covered in lecture(synchronization, IPC, gRPC). Projects 1 and 3 were in C, and 4 was in C++. I was comfortable with both so it was never an issue for me, but if you aren’t familiar, it might be difficult to pick up quickly. Overall I probably spent around 40 hours per project, and got full credit on each of them. Make sure to read Piazza posts and the Slack channel for tips, and don’t be scared to ask questions! The test cases weren’t particularly difficult to pass, and you have plenty of submissions. Any test case that fails gives you nice error messages that help you understand where you went wrong. The exams were mostly multiple-choice with some matching. I found that they were heavily based on memorization, and the projects don’t really help with the exams. Make sure to understand the lectures thoroughly and use lecture notes provided online to fill in any gaps. Be sure to ask in Piazza or Slack as well. Overall, I found the exams relatively easy. In general, this class helped me learn so much more about what the role of an operating system is, and made me a far better programmer regarding managing dynamic memory and multi-threaded applications. I learned so many things in this class! It is hard to put in words just how much I learned. If you like low-level programming and want to learn about the intricacies of the machines we take for granted, take this course\! Rating: 5 / 5Difficulty: 3 / 5Workload: 15 hours / week - Qhteq7WngCJs5IrUJuNRwg== December 22, 2025 fall 2025 [Database Systems Concepts and Design](https://www.omscentral.com/courses/database-systems-concepts-and-design/reviews) This was my first course at OMSCS, and I chose to take it despite the not-so-great reviews. I was pleasantly surprised by the experience. For context, I work as a data specialist at a small institution and come from what I would call a flawed CS education, so even though I completed a CS bachelor's degree, I consider myself much closer to a career switcher than a traditional CS student. The class is well organized with a clear grading breakdown: Four exams, each worth 12.5% (50% total) A three-phase final project worth approximately 35% Participation worth 15% Course Components Lectures: The lectures are pretty good and cover everything you need to know about database systems fundamentals: Relational Algebra and Calculus, Normalization, SQL basics, ER design, Relational Mapping, etc.. They do a good job of preparing you for the exams. There are also methodology lectures that clearly explain what's expected for each phase of the course project. Exams: The exams were fair, though attention to detail is VERY important (I can't stress this enough). Please read each question carefully (multiple times if necessary). Practice exams are invaluable for preparation. If you can complete the practice exam without looking up the answers, you should perform well on the actual exam. Project: This is the most variable component of the course, as your experience will depend heavily on your group. I was fortunate to have an amazing team, and everything went smoothly, making the workload quite manageable. However, I can easily see how a difficult group dynamic could make the project extremely challenging. Be proactive early in the semester to find a strong group. While you can't predict who might drop, aim to form a team with diverse skills. Ideally, someone experienced with databases (both conceptual design and SQL), someone with backend expertise, and someone with frontend skills. Yes, frontend skills. The Project is a full-stack web application. Grading Expectations This course is generally considered an easy B but a challenging A. There appears to be no curve. I scored in the 90s on everything and earned an A (94%). If you struggle on even one exam (and the average on the final was in the 70s) an A becomes difficult to achieve. Keep this in mind before registering; I'm providing this as helpful information, not to discourage you. Final Thoughts Overall, I think this is an excellent course. I highly recommend it if you've never taken a database class, love databases, or want to solidify your understanding of database fundamentals. However, this course may not be ideal if you're seeking advanced database topics, looking for an easy A, or prefer to avoid group projects. Rating: 4 / 5Difficulty: 3 / 5Workload: 15 hours / week - PwTXmUqnoUMXfduKETMS/A== December 22, 2025 fall 2025 [Machine Learning for Trading](https://www.omscentral.com/courses/machine-learning-for-trading/reviews) My background: first semester in OMSCS, CS undergrad, and 5 yoe as a software engineer. No ML or AI knowledge prior to this course. This course was awesome. The lectures were interesting, the projects were well-defined and fun to work on. I would recommend everyone take this course. It's the perfect intro to ML concepts. My only tip is to make sure to start assignments early, especially the final 2 projects. This course does use a lot of Python and Numpy. I have no professional experience in Python and had to re-learn a lot of it. Really not a big deal if you know how to code in any other language. Rating: 5 / 5Difficulty: 3 / 5Workload: 15 hours / week - PwTXmUqnoUMXfduKETMS/A== December 22, 2025 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) My background: first semester in OMSCS, CS undergrad, and 5 yoe as a software engineer. This class was a great intro into HCI and the OMSCS program. I am not the best writer so the amount of written assignments almost scared me away. The assignments have clear directions and even as a weak writer you are basically guaranteed an A as long as you clearly follow the instructions. The group and individual projects are basically the same: practicing the design lifecycle using strategies that are well-covered in the course material and writing A LOT about it. Make sure to follow the directions closely and include everything they ask for. Overall, group projects put you at the mercy of your teammates. Don't leave your group up to chance: pick your team early to find proactive students to secure your A. I finished the class with an A but the team project almost sent me down to a B as most of my teammates didn't follow the directions and one didn't do anything. Rating: 4 / 5Difficulty: 3 / 5Workload: 15 hours / week - FuW7Lf2BVGTKYArYj7f7ew== December 22, 2025 fall 2025 [Artificial Intelligence](https://www.omscentral.com/courses/artificial-intelligence/reviews) This class provides a broad overview and introduction to topics in Artificial Intelligence. Because of the broad nature of the class, most topics to not build on what came earlier in the class. The first half of the class covered more traditional applications of artificial intelligence, such as search, game playing, and constraint satisfaction. The second half of the class covered probability, Baysian networks, and deep learning. The last time I took a probability course was many, many years ago and my knowledge was not adequate for the second part of the class and resulted in a frustrating experience. The class was well run and the TAs were active in the forum. While I didn’t enjoy the class, I did learn a lot and developed a better understanding of the AI buzzwords that are popular now. Rating: 3 / 5Difficulty: 4 / 5Workload: 15 hours / week - FuW7Lf2BVGTKYArYj7f7ew== December 22, 2025 summer 2025 [Introduction to Information Security](https://www.omscentral.com/courses/introduction-to-information-security/reviews) There was nothing to work on for the first week of class. I made use of the extra time by learning how to use Wireshark more effectively. If you can learn how to filter and use the tool, it will help a lot with the Man in the Middle project. This class had no exams or quizzes; it was all projects. The hardest part of this class is the constant pressure of a new project due every week, especially if you are not familiar with the topic that week. Compared to classes with more traditional programming projects it can be frustrating. There often isn’t the ability to make incremental progress, you either get the solution or you don’t. Overall, I enjoyed the class. If taking in the Fall or Spring the relatively light workload would pair well with another class. Rating: 3 / 5Difficulty: 2 / 5Workload: 12 hours / week - sO8OJlQ/P8sVDM5eftGHRA== December 22, 2025 fall 2025 [Network Security](https://www.omscentral.com/courses/network-security/reviews) tl;dr - Take IIS and skip this course. IIS is a much better course overall. NS is simply not worth your time or money. I have a lot to say about this course, but I'd rather keep this short and just hit the highlights. I'll start with the good and say that the TA's are great and helpful. Truly the one good thing about this course. Second, the malware section of this course is better IMO than the one in IIS. I think they should scrap NS, use the malware section from NS for IIS, and call it a day. I felt NS was a colossal waste of time. I only had to spend about 5 to 6 hours each week to get an A. The material is ancient by cybersecurity standards and references material that was published before I even started working in the industry. This isn't to say that information can't still be correct if it's old, but technology has changed so much since a lot of this course was written that I frequently struggled to find the relevancy. The projects are a mix between okay and outright terrible. I think the biggest letdown was the ML project. The IIS ML project did feel a little forced into the course, but at least you learned about encodings, training and testing, and fundamentals on how ML works. In this course you get to add some python to a tool that the professor helped author back in 2006! That's it. That's your ML project. My two cents is this: do not take this course. GATech should seriously consider either reworking this course or scrapping it altogether. It's a waste of students effort and money to have something in a graduate program that I think barely passes as undergraduate. I highly recommend Advanced Topics in Malware Analysis if that's your thing. Otherwise, just take something else, anything else. AIES was better. Rating: 1 / 5Difficulty: 1 / 5Workload: 5 hours / week - ipe1i/snfsp+HDoZP/0IFw== December 20, 2025 summer 2025 [Deterministic Optimization](https://www.omscentral.com/courses/deterministic-optimization/reviews) *Taken Fall 2025* The reason I am leaving a review is because I saw a recent negative post about this class and wanted to chime in. Firstly, as someone who enjoys math, I really enjoyed this class. I think the class is well-structured and the homework reinforces the materials since it forces you to apply course concepts. You learn to how to model problems as optimization problems and then methods for solving said problems. It was interesting and felt very practical. I didn’t think the material was hard, but it definitely assumes some familiarity with derivatives and linear algebra. Secondly, I’m not sure if there was a curve at all. My assumption was that there was no curve. If there was one, then it was not mentioned at all by staff. I managed to get an A without any curve. Getting an A is definitely doable, but it is stressful because of how heavily weighted each exam is. I firmly believe that if you did the knowledge checks and practice exams, like really really studied them, then you’d be well-prepared for the exams. Lastly, the material is definitely relevant. Linear programming might not be prominent in everyday life, but some concepts definitely appear frequently. If your job is to model problems and solve them, then this course is relevant. If you’re in the ML space, then you’re bound to encounter optimization problems since the goal is to either minimize error or maximize performance. See Andrew Ng’s lectures on regression/classification and you’ll see the importance of optimization. Rating: 5 / 5Difficulty: 2 / 5Workload: 8 hours / week - mWlYV8RYUV9ANY+ovth3FQ== December 20, 2025 summer 2025 [Reinforcement Learning and Decision Making](https://www.omscentral.com/courses/reinforcement-learning-and-decision-making/reviews) Actually took course in Fall 25, but that option wasn't listed on form. Giving the course a 1 because the same feedback is given by almost every student and no attempt has been made to fix it. My feedback is pretty much the same as every other student. Lectures are old and disjoint from projects. No need for the final to be as hard as it is and very taxonomic/unrelated to projects. Ultimately not much better than just seeking out and doing RL projects yourself. For a grade I got near perfect scores on the first three projects and then phoned in the last project and the final. That was enough to get a B, which is all I needed to get reimbursed from my company for the course. Median on the final was ~48%. Rating: 1 / 5Difficulty: 5 / 5Workload: 25 hours / week - KU1E6SWndsiNMKo6qjvF0w== December 20, 2025 summer 2025 [Deterministic Optimization](https://www.omscentral.com/courses/deterministic-optimization/reviews) This course sucks in the way that it forces curve. Only x % got A no matter what. I don’t agree with some comments here praising the course design. It’s pretty much all about linear programming and old school stuff and to be honest, it has almost 0 value in real practice. Rating: 1 / 5Difficulty: 2 / 5Workload: 5 hours / week - u3nsnLbC8JcfIhZUgs8zlg== December 19, 2025 summer 2025 [Introduction to Health Informatics](https://www.omscentral.com/courses/introduction-to-health-informatics/reviews) Fall 2025 First half of the course with labs, quizzes and lecture videos were great. My average time spent was about 5 hours/week Second half of the course with the group project was a disaster because my teammates were not familiar with git and web development plus not willing to spend the time to learn them. Ended up doing the group project myself entirely. I heard that other people enjoyed their group project because they had amazing teammates. Your group project experience really depends on your teammates. The course would have been a lot better if I had better teammates. Doing the course project as a solo was prohibited. Choose your teammates wisely. Pick those who have actually web dev/full-stack experience. No amount of gatech courses taken would be a sufficient substitute of that experience. I have heard horror stories of group projects in gatech previously. This time I am the survivor who experienced it first hand. Rating: 5 / 5Difficulty: 1 / 5Workload: 20 hours / week - Y//78ivuAYK34qoqqIUJsA== December 18, 2025 summer 2025 [Introduction to Computer Vision](https://www.omscentral.com/courses/introduction-to-computer-vision/reviews) ## Actual term: Fall 2025 Final grade: A I'm a CS undergraduate and even though I'm not exactly new to computer vision (as I've already taken Deep Learning, and learnt a bit of geometric vision a few months ago) I'm far from actually knowlegeable in the subject. My overall experience was positive. There is a ton of material and a ton of work since the assignments require knowledge about the algorithms, implementing them from scratch, and lots of tuning to make them work, at least for grading. Assignment 3 in particular was the most demanding and lengthy, and it was the only assignment where we were given a 2-day extension. I felt kinda burnt out after this assignment and "slacked" in the next two (I did everything except the extra credit sections). The final exam was comprehensive but fairly reasonable in difficulty. It's open everything (except for direct answers, especially from LLMs) and multiple-choice. It is actually just an excuse to review the material (and they say so). I cannot comment on TAs or the instructor as I never needed them. Everything was covered in the lectures (with an additional independent reasoning), READMEs and FAQs. I don't understand people complaining about unclear expectations, rubrics, etc. They tell you everything you need to know, and expect you to study just a bit for yourself (as should be expected). The only parts where I was not given credit where the sections I didn't answer, and the only parts where I was given partial credit were sections that I intentionally didn't want to answer more precisely (especially those requiring microscopic fine-tuning). I did Action Recognition for the final project and it felt like an additional problem set (and it actually was an extra problem set many years ago) with an extra workload since you have to create your own (numeric) dataset out of some videos, but the algorithm itself is really straightforward. I think that this course is only a must-take course if you're really serious about computer vision and think that deep methods can't solve everything. Rating: 5 / 5Difficulty: 3 / 5Workload: 18 hours / week - LrS4aqhyfWY1FWNImRt0sw== December 18, 2025 fall 2024 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) Non-CS STEM major (Electrical Engineering), no coding experience in the past 5+ years. Took GIOS as the first class in the program. This was a tough class that consumed a lot of time, especially because I had to learn C, C++, and gRPC on the fly. However, this class teaches you a lot about how operating systems work and makes you a strong (or stronger) C programmer by the end. I would highly recommend this class if you are willing to learn and are prepared to put in the time. Project 1 (Pr1): I spent the most time on this project because I had to learn how to code in C and read Beej’s Guide to Network Programming. This project is broken into four parts. Each part is designed to help you learn what is needed for the subsequent part, and by the end, you can create a multi-threaded getfile library. I spent a significant amount of time compared to others, likely because I had no prior C experience and hadn’t been coding in recent years. • Part 1: 10 hours • Part 2: 10 hours • Part 3: 80 hours • Part 4: 80 hours *** Project 3 (Pr3): For this project, I spent a lot of time thinking about the design, referring to comments on Slack to understand how other students were approaching the problem, and asking questions to verify my understanding of the project and my design. Writing the actual code was less time-consuming compared to Project 1. • Part 1: 20 hours – This part was simple and helped me get familiar with the CURL library. • Part 2: o 20 hours – Researching and coming up with the design. o 40 hours – Writing code, implementing, and debugging. *** Project 4 (Pr4): This was the hardest project for me, even though many others thought it was the easiest. It may have been easier for students who already had exposure to gRPC or something similar. If you have time after finishing Project 3 and before starting Project 4, I highly recommend spending some time learning about gRPC—it will help a lot. • Part 1: o 20 hours – Learning how gRPC works and understanding examples. o 10 hours – Writing the actual code. • Part 2: o 40 hours – Figuring out how the overall library was intended to work based on the provided codebase. While I had to do this for all the projects, this one was particularly hard because it was complex, and there were so many different .ch files to read and fully understand before I could grasp how the DFS was intended to work. o 30 hours – Writing the actual code. *** Midterm Exam: The midterm wasn’t too hard. Just keep up with the lectures and make sure you thoroughly understand the practice exam. *** Final Exam: The final exam was much more challenging. The amount of material covered on the final is roughly twice what’s covered on the midterm. By the time I finished Project 4, I was six lectures behind, and I had only about 10 days to prepare for the final. Trying to cram all the material into a short amount of time, like a week, was brutal. Since I calculated that I only needed 55+ points to achieve 84% or higher overall, I took the exam without adequate preparation—and that was a big mistake. I spent several days anxiously waiting for the final exam grade because I thought I had bombed the test. *** Final Thoughts: I agree with the strategy of starting projects as soon as they are posted. As long as you put in the time, refer to the Slack channel for clues when you get stuck, and ask questions, you should be able to score 100% on all the projects. If you get 100% on all projects and score at least the median (~75%) on the exams, you should be able to earn an A, which typically has a cutoff of 81%-84%, depending on the class average. If I had to retake the class, I would allocate 1 hour per day to studying or staying up to date on lectures, even while working on projects. Cramming everything before the midterm and final because I dedicated all my energy to getting perfect scores on Gradescope was not a smart idea. Since the three projects account for 45% of the total grade and the two exams account for 50%, allocating time to exam preparation has a better ROI for achieving a good grade. *** My Results: I ended up with a grade well above the curve for an A (82% for Fall 2025). • Projects: Full scores (~100%) on all three. The class median was also nearly 100% for all projects. • Midterm: Scored in the 75th percentile, well above the median. • Final: Scored in the 50th percentile, around the median. *** Rating: 5 / 5Difficulty: 4 / 5Workload: 25 hours / week - ZduXZVe+NcBIRDua2dy92A== December 18, 2025 summer 2025 [Machine Learning](https://www.omscentral.com/courses/machine-learning/reviews) This review is for Fall 2025 term. Just finished the class with an A. It has been a tough class, probably the most laborious and time-consuming among all I’ve taken so far (see below). One piece of advice to those who are going to take this class: have a LOT of time on hands to spend on this class. No matter what your background is, if you have time to spend on this class you are likely to succeed. Also, when you write your reports, it helps to have a dedicated “Hypotheses” section with a few numbered hypotheses that are drawn from the course material or papers (explicitly sighted) and then in the Results/Conclusion sections you explicitly accept or reject each of these numbered hypotheses. Background: 7th class in the program (after AI4R, KBAI, ML4T, AI, DL and CN). The material in ML4T, AI and DL was very useful as a pre-courser for ML - most items in this course looked familiar which helped a lot. Prior to that – no/minimal CS but some STEM academic background (from about 20 years ago). I do have some experience with academic writing and LaTeX, both the previous academic background and from current work. Other than that, demanding full-time on-site job, family and other obligations. Taking the program mostly for self-development, not for career change (although – who knows nowadays). I value the courses I take as the ratio of how much new I learned vs. the amount of time and stress it took. For this class, the denominator goes to infinity whereas the numerator, while large, is finite. Hence, it was not my favorite class (so far, the best class for me was AI4R, and by far the worst – KBAI (please do not waste your time with this class)). The good: - Professor LaGrow and all teaching staff do their best to encourage the students. You may (and most likely will) feel miserable at times but they don’t want you to. With the number of extra points, reviewer response, etc. anyone who spends the proper time on this course can succeed. - The material is quite interesting. Maybe not the very cutting edge but essential. - I obtained (or started obtaining) a very useful skill: using AI code generating tools to produce the code that does the desired analysis. I would not be able to write all the code for all the analysis by myself – nor apparently this is needed any longer. Not so good: - I felt that the amount of material was overwhelming. With its breadth, it was not possible to dive deep enough. Every 3 weeks a super large topic was covered, and in these 3 weeks, one had to (preferably) understand what’s going on, write (or generate) bunch of code, run it on two very different datasets (one of which is huge and super noisy), design and run your experiments that should test a few dozen things and then write an 8-page report. - The course puts an emphasis on academic writing. Although undoubtfully an important skill (plus helps to organize the subject knowledge), I believe in this case this emphasis was excessive. I’d much rather prefer to understand the subject matter deeper. - There is a lot of debate on the quality of the lectures. Some love this format, some hate it. I would have been OK with it if the lectures were not so long. With the number of things to do for the course, I could not afford to spend several hours a week listening to the lectures. It feels that the same could have been said in a more concise manner. As many students complain, the report grading feels random. My grades were 89, 89, 62 (+19 recovered in reviewer response), 101 but the structure of report 3 mimicked that of 1 and 2. The main complaint of Report 3 grader was that there was no a dedicated section with the “numbered” hypotheses (although they were formulated in the Methodology and Data sections of the report). Most likely the need for the separate section was discussed in the OH (that I mostly could not attend) but there was no such requirement in the project description or the FAQs. What I’m trying to say is that I had no feeling at all about what grade I was going to get for the reports (I personally felt that my report 3 was stronger than 1 and 2). All in all, I’m not regretting taking this course, just wish it was not taking ALL my time (and more). Rating: 4 / 5Difficulty: 5 / 5Workload: 30 hours / week - 8/lglYFHPFGhVYhCsoaRaw== December 17, 2025 spring 2025 [Introduction to Graduate Algorithms](https://www.omscentral.com/courses/introduction-to-graduate-algorithms/reviews) This class is very exam heavy, so go in knowing exactly what you’re signing up for. Exams are 90% of the grade, while the formatting/logistics/content quizzes are pretty easy and make up the remaining 10%. Even if the homeworks are optional, do them. They’re one of the best ways to understand how the exams are structured and what level of precision is expected. Also, attend office hours. They help way more than you’d think. If you believe you were graded incorrectly, submit a regrade request. A lot of students don’t do this out of laziness. Just be aware that the entire question gets re-reviewed, so if they find an additional mistake you might lose points too. Still, if you’re confident, it’s worth it. You genuinely need to study hard for this class. You can’t rely on Chat GPT or shortcuts to pass cause this course really tests understanding. Proctoring is also very strict, so follow every instruction carefully or you’ll risk unnecessary penalties. This class is doable, but it requires serious effort. No slacking. It honestly feels like the ultimate boss of OMSCS. For reference, I got 35/60 on the first exam, 49/60 on the second, and 42/60 on the third. If you do poorly on the first exam, don’t get discouraged-it’s very possible to recover if you adjust and study harder. One final warning: formatting and wording matter a LOT. The TAs expect answers in a very specific format, and being even slightly unclear can cost you points. One wrong word can mean deductions, so be extremely precise and explicit in your exam responses. Overall: tough class, high workload, but passable if you hustle and put in the work. \-NP Rating: 3 / 5Difficulty: 5 / 5Workload: 30 hours / week © 2026 OMSCentral. All rights reserved. [](https://www.buymeacoffee.com/omstech)

### 100 Most Recent Reviews - Bt0s2h6ErpUV5XlCbPyEcg== March 24, 2026 spring 2026 [Introduction to Analytics Modeling](https://www.omscentral.com/courses/introduction-to-analytics-modeling/reviews) Dreadful, actually pathetic that a top 5 school allows this course. The lectures too sparsely cover too many models, the homework are LLM coding exercises with no feedback beyond thumbs-up emojis or trivial formatting criticisms, and the exams are largely indecipherable. If you want a basic introduction to ML, statquest is an order of magnitude better than 6501 and 100% free. I am astounded this class is rated so high and chalk it up to people with CS undergrads or people with low standards. This course is so bad but rated so high I withdrew from the entire program. Most of the other required courses are in the low 2s. Shocking, because I can't even imagine how bad they must be after taking this one. Rating: 1 / 5Difficulty: 2 / 5Workload: 10 hours / week - J2D54Vgzw983EqL0aj+WkA== March 23, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) Lectures: Lectures from Prof Riedl are mostly good. Meta lectures are mostly terrible - presenters just reading dense slides at the camera. Lecture errata are in a separate Word document instead of just being added below the actual lectures. Also, lectures can only be viewed through Canvas instead of Ed Lessons for some reason. Quizzes: Weekly quizzes proctored with Honorlock (closed everything). Quiz weighting is 10% as of spring 2026. Sometimes the questions are worded quite poorly. Exams: 20% midterm, 20% final, closed everything and proctored with Honorlock as of spring 2026. I’ve only taken the midterm so far. The midterm exam was a mix of multiple choice single answer, multiple choice multi-answer (sometimes with MANY options), and free response. Not many questions - make a mistake on one question and your overall grade will take a substantial hit. A practice midterm was given, but much easier than the actual midterm. Instead of curving the midterm, a "midterm retake quiz" was offered so students could try to improve their scores on a few select questions that were poorly written. Homework: Assignments 1-4 are too simple and the tests are not rigorous. You can get 100% without really understanding. The professor has admitted this is the reason for reducing the weight of homework assignments in the final grade. Between 2 to 8 hours to complete each one. Most of the time is trying to understand the misleading instructions or figuring out the bugs in the code that is provided (and you aren’t supposed to modify). Course staff: TAs are mostly slow to respond if they respond at all. The head IA (initials FPG) is actively unhelpful and refuses to respond to any questions regarding course policy interpretation. Time commitment: Mostly low outside of exams. tl;dr: No longer the easy A that it was in previous semesters. Take CS7643 (deep learning) instead, which covers a lot of the modern NLP architectures in more depth and has amazing TAs. Rating: 2 / 5Difficulty: 3 / 5Workload: 10 hours / week - HAguuo5dzJMJGPaXXeclcA== March 22, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) Hmm, I am feeling rather ambivalent about this course as a whole so far. The lectures by Dr Riedl were fantastic, and they have helped me gain a much better understanding of tricky NLP models like transformers, seq2seq, LSTMs etc and the lecture content was presented superbly by the professor. The same cannot be said for the Meta lectures unfortunately. The saddest part about this course is mainly in relation to the rather vague and questionable option choices given as part of the quizzes and exams. Some of the questions had typos which led to a complete mismatch in expectations of the required answers between students and the grading rubric, while quite a few of the quizzes tested definitional questions using vague options which defeated the purpose of assessing a student's knowledge for the content. I would say that the course would be in a much better shape if the quizzes and exam questions were more polished in terms of precision. I understand the intent behind the vagueness (defeat the use of LLMs) but given the closed book nature of the exams, perhaps having questions that were more directly worded can make the test taking experience and assessment of knowledge more pleasant and accurate. Rating: 3 / 5Difficulty: 3 / 5Workload: 8 hours / week - awYgiOyV8rynxZPMkPOQoQ== March 22, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) Whoever is leaving the 1/5 reviews is just mad because they did poorly on the exam because they didn’t prepare enough. Part of taking a graduate course is acting like an adult and taking personal responsibility for success and failures. This person flamed out in the ED forums, was disrespectful, and acted like a child. Do not pay attention to their reviews — Dr Reidl is great, the TAs were helpful and accommodating. More importantly, the material was very interesting and well explained. pS grow up Anonymous Duck. Rating: 5 / 5Difficulty: 4 / 5Workload: 12 hours / week - V3zNSIx3Ly3kbWC2XYV9NQ== March 19, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) The exam design is atrocious. Between the irresponsible TAs and the word games posing as questions, this course has become a complete train wreck. The TAs are obsessed with multiple-select questions—one even had eight options! I honestly suspect these were AI-generated. The TAs should really try taking their own exams before subjecting us to them.The exam design is atrocious. Between the irresponsible TAs and the word games posing as questions, this course has become a complete train wreck. The TAs are obsessed with multiple-select questions—one even had eight options! I honestly suspect these were AI-generated. The TAs should really try taking their own exams before subjecting us to them. Rating: 1 / 5Difficulty: 5 / 5Workload: 10 hours / week - Xufos/FC+l9HofxMOEzTTA== March 13, 2026 fall 2025 [Machine Learning for Trading](https://www.omscentral.com/courses/machine-learning-for-trading/reviews) Overall I liked the material of this class although I have to admit it just reinforced that algorithmic trading is a complete losers game unless you are one of the big quant firms. My one complaint is I got a 20/50 on one project because I used a table instead of a graph, and I had two of my paragraph headings swapped. This dropped my grade by about 5% which was pretty lame. I felt like the grading much like many OMSCS classes is subject to capricious and highly variable graders. Rating: 3 / 5Difficulty: 3 / 5Workload: 8 hours / week - LdUCwaravOrZ37Up9FutNA== March 11, 2026 summer 2025 [Digital Marketing](https://www.omscentral.com/courses/digital-marketing/reviews) This has to be the easiest course in the program. The entire course is opened up immediately. It took about 2 1/2 weeks to comfortably complete the entire course. My only two pieces of advice- 1. Read the requirements for posting. I believe people got 0s on simple posts because they didn't bother to follow the basic rules of what not to do. 2. Put some effort into preparing for the exams. They're relatively heavily weighted. I did not do well on the midterm because I did 0 studying. Then I put in a little effort on the final and cruised. You will not get a study guide for either test (yes, even if you wait for the "scheduled" test week) so you'll have to review everything for that half of the course. After that, just monitor your email every week or so to watch the grades roll in. Rating: 4 / 5Difficulty: 1 / 5Workload: 2 hours / week - LdUCwaravOrZ37Up9FutNA== March 11, 2026 spring 2026 [Computer Networks](https://www.omscentral.com/courses/computer-networks/reviews) I came in with network experience, so the first few weeks weren't terribly exciting or new for me. However, if you are new to networks, I think the information can help understand what's going on behind the scenes. The TAs were available throughout the course. There was a lead TA for each project and they took the time and effort to make interesting problems to solve. I would recommend decent Python knowledge if you don't want to struggle mightily with the projects. Nothing dramatic, but understanding inheritance will go a long way. The lectures were an abomination. The slides were fine and provided information. But the actual recorded video may have been recorded during a hostage situation. It was not motivating. And the professor popping up twice - once before the midterm and once before the final - to review quiz questions that aren't related to the exam didn't seem terribly useful. The least interested person in the class should not be the professor. The exams were a minor annoyance. If you went through the slides you'll do fine overall. Overall, there were interesting parts to the course. Rating: 3 / 5Difficulty: 2 / 5Workload: 8 hours / week - FNSkyjhjdkDAZ1hbqpRZkQ== March 11, 2026 fall 2025 [Reinforcement Learning and Decision Making](https://www.omscentral.com/courses/reinforcement-learning-and-decision-making/reviews) Check out the grade distribution, this class has gotten worse, people are getting more Cs and Ds now. Not recommended for people with a full time job. I was counting on "the curve" to get a C and graduate as it was my last class. There wasn't any curve that people speaks of during Fall 25. Office hours was a waste of time, lectures was useless. I should of use PPO for everything and it would of make my life much easier, but I chose to experiment with different algorithms. You will learn absolutely nothing from the teaching staff. Count on reading a lot: Sutton RL book end to end, MARL book, and the Grokking book for the algorithms. What you paid for is for someone to read your papers and give you a bad grade because you didn't meet their hidden rubrick. I dropped this course twice before during the registration period. I finally decide to go with it thinking the new staff is better. BIG MISTAKE. I got to take a 11th class now. Rating: 1 / 5Difficulty: 4 / 5Workload: 30 hours / week - Q7vQ4S8LzdYPLTOEp+OplQ== March 10, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) Wish I could enroll for only half the semester. Rating: 1 / 5Difficulty: 5 / 5Workload: 19 hours / week - wzuTgVDUXQlOr0c6l20xdw== March 7, 2026 fall 2025 [Introduction to Health Informatics](https://www.omscentral.com/courses/introduction-to-health-informatics/reviews) Very easy course. Projects weren't time consuming, quizzes were open note, no Honorlock either. Got an A with no struggle. Final project was a little difficult, it really depends on who you get for your group members. But don't slack off, or otherwise you'll be spending multiple hours a day trying to get all the deliverables done as the course finishes. Rating: 4 / 5Difficulty: 2 / 5Workload: 4 hours / week - Q7vQ4S8LzdYPLTOEp+OplQ== March 6, 2026 spring 2026 [Natural Language Processing](https://www.omscentral.com/courses/natural-language-processing/reviews) Had so much fun with the exam and Meta lecture. Rating: 1 / 5Difficulty: 5 / 5Workload: 15 hours / week - RwC4XfLWS/UqhqfB5w2qFA== March 3, 2026 fall 2025 [GPU Hardware and Software](https://www.omscentral.com/courses/gpu-hardware-and-software/reviews) The GPU HW/SW course is a well-balanced class that provides hands-on experience with both GPU programming and GPU microarchitecture, along with a bit of compiler-style dataflow analysis. The workload is moderate, the projects are well-scoped, and the TA team is exceptional - making it a strong elective for students interested in systems, architecture, or parallel programming. Projects The course is built around five projects, each highlighting a different part of the GPU stack. Project 1 – CUDA Matrix Multiply (Intro Project) This is a basic introduction to CUDA and the ICE cluster environment. The assignment is just a warmup to get familiar with the toolchain and cluster workflow. Anyone with basic C/C++ experience should complete it quickly. Project 2 – Bitonic sort in CUDA This is the toughest project, but also the most rewarding. You implement Bitonic sort in CUDA and optimize for performance. The optimization component adds some challenge, but the project is very doable and well-defined. Many students consider this the highlight of the course. Projects 3 & 4 – GPU Hardware Simulation These were two separate assignments where you modify a simplified GPU simulator to explore architectural concepts like: -modeling GPU cores -adjusting pipeline/latency behavior -experimenting with warp scheduling strategies These projects aren’t conceptually difficult, but matching simulator output exactly can be tedious. Fortunately, full precision matching is not required; you receive 95% credit as long as your statistics fall within a small tolerance. As of the current semester, these two have reportedly been merged into a single Project 3, and a new Project 4 has been introduced related to ML (attention mechanisms). I don’t have specific details on that new assignment, but historically the simulator projects have been very manageable. Project 5 – Dataflow analysis (Reaching Defs & Liveness) Despite the terminology, this is not a compiler-heavy project. You analyze a small set of instructions and compute reaching definitions and liveness information. Students without compiler backgrounds typically do fine. It’s systematic rather than difficult. Lectures, Quizzes, and Exam The lectures are (very) short and focus directly on the material needed for the projects. They are not exhaustive or deeply theoretical, but they give you enough context to succeed. Quizzes are straightforward and (at least previously) open book. There is one final exam worth 10% of the grade. It was fair and consistent with the quizzes and lectures. There is a policy requiring at least 90% overall, and at least 40% on the final exam to earn an A in the course. TA Support The TA team is one of the strongest aspects of the course. The head TA (Scott) is exceptionally responsive, and the entire team is helpful, knowledgeable, and engaged. Ed support is fast and detailed, which significantly improves the project experience. Workload & Overall Difficulty Overall, the effort level is medium to medium‑low (likely medium now given the new project,which probably increase the course load by 15-20%). The projects are interesting, the course is not stressful, and the pacing is comfortable. It’s a great “systems” elective that blends GPU software, architecture, and light analysis without overwhelming students. Final Verdict Highly recommended! Especially for students interested in GPU programming and architecture, and performance analysis and optimization. The course offers a meaningful hands-on experience with a manageable workload, excellent TA support, and projects that are both fun and practical. Rating: 5 / 5Difficulty: 3 / 5Workload: 12 hours / week - VCDIClRtIFtPSzHF+7M+iA== February 28, 2026 fall 2025 [Advanced Internet Computing Systems and Applications](https://www.omscentral.com/courses/advanced-internet-computing-systems-and-applications/reviews) https://www.ratemyprofessors.com/professor/1651694 The reviews on ratemyprofessors matches my experience in the class. Writing heavy (8 pager every week). Unclear rubric and flags you for AI even if you didn't use AI. Professor does not care and says Canvas' AI detector decision is final. Leading to a situation, where it is better to have grammar/spelling mistakes in your paper to have a lower chance of getting flagged. The grading criteria for assignments is extremely vague and the feedback you get from course staff is surface level. Rating: 1 / 5Difficulty: 4 / 5Workload: 15 hours / week - fCzz1wtfcs0nTjWI8fFOxw== February 23, 2026 spring 2026 [Machine Learning](https://www.omscentral.com/courses/machine-learning/reviews) I took (and withdrew from) this class as my 6th in the program. I was taking this course as an elective. Don’t do it\! This course is awful. The assignments might be worthwhile exercises if you already know ML, but otherwise it’s more like busywork or hazing. In a single report, the timeline for which is about 3 weeks, you must implement then “analyze” and discuss several different models on two datasets. This could be useful, except the course content does not at all prepare you for what’s in assignments. Thus, in order to be able to somewhat genuinely write on these topics, you must spend hours and hours researching outside of the course content to get a handle on what the assignment is asking you to do. Then, you must implement these models, which might take hours to tune/run, and write a report discussing all of these topics you have to self-study. This genuinely could work as a fruitful learning experience, except you’re also burdened with quizzes and an exam. These are more closely related to the course content, but again totally disjointed from the assignments. So, in the same 3 week span, in addition to the time you must spend on self-studying for and working on the report, you must watch lectures/read/study in preparation for the proctored unit quiz. I submitted the first report, having spent \>40 hours on it, and felt like I hadn’t learned anything. My writing felt like slop, just BS I put down to get through the assignment. In every other course I’ve taken thus far, whenever I finished a very difficult assignment, I felt a sense of pride, achievement, and fulfillment. Not in ML. Rating: 1 / 5Difficulty: 5 / 5Workload: 40 hours / week - 4YpbCjbYv2B3IvKU2aXZhg== February 23, 2026 fall 2025 [Data Mining and Statistical Learning](https://www.omscentral.com/courses/data-mining-and-statistical-learning/reviews) As others have pointed out, the lectures feel like a waste of time. The quizzes are also not that useful and closely resemble (and often directly replicate) the practice questions, so as long as you've done those beforehand, you should manage fine. I’m giving a neutral rating mainly because I found the homework and project enjoyable, which balance out the more mundane aspects of the course. The flexibility to choose your own topic and dataset makes the project engaging, and I got to follow my peers' train of thought through peer reviews (yup, there are peer reviews). Overall, the course builds reasonably well in terms of content and expectations, which is a decent follow-up to ISYE6501. Rating: 3 / 5Difficulty: 4 / 5Workload: 8 hours / week - 4YpbCjbYv2B3IvKU2aXZhg== February 23, 2026 fall 2025 [Special Topics: Data Analysis for Continuous Improvement](https://www.omscentral.com/courses/special-topics-data-analysis-for-continuous-improvement/reviews) Mixed experience. The course didn’t really feel like it met graduate-level requirements since the material was quite basic and introductory. I was also somewhat frustrated with how my final project went, since there appears to be a specific structure and response preference that leads to better grades - it could work out if you focus on more 'traditional' sectors like manufacturing/supply chain, but may get marked down if you do something a bit more unorthodox. I also don’t think the green belt certification is particularly meaningful in today’s context (may even be a red flag to have it in your LinkedIn). Rating: 2 / 5Difficulty: 2 / 5Workload: 4 hours / week - cwsy/21t9yRCKivsAqMLfA== February 22, 2026 summer 2025 [Advanced Internet Computing Systems and Applications](https://www.omscentral.com/courses/advanced-internet-computing-systems-and-applications/reviews) When I looked it seems like there's other reviews for this course but they don't show up? I didn't take the course I'm just aware that you should look up the professor on RateMyProfessor before you take their class. It's Ling Liu the current prof. https://www.ratemyprofessors.com/professor/1651694 4% would take again, nuff said. Rating: 1 / 5Difficulty: 5 / 5Workload: 15 hours / week - GOgTqGxWG9t1dh0dOQbgDQ== February 8, 2026 fall 2025 [Software Development Process](https://www.omscentral.com/courses/software-development-process/reviews) Overall grade: A (99.56%) Background: BS in Computer Science. 3 years of STEM work experience (not as a software engineer). Lectures: The lectures are still from Professor Orso, even though he has moved to a new college. The videos are very high quality, and I enjoyed listening to the lectures. The material is presented in an engaging way that makes it easy to follow. In addition, the instructors include a set of notes from a previous student, which were still up-to-date with the current version of the course materials from what I could tell. Exams/Quizzes: There are no exams or quizzes in this course. Assignments: There are 6 individually-completed assignments, 1 group project, and 1 individual project. The first 5 individual assignments are easy points. The 6th one is significantly more tricky - more like a set of mini puzzles. However, once you figure out the answer, you will know it is correct. I caution that a previous reviewer of this class mentioned something along the lines of "you will lose more points than you would gain if you attempt and fail the extra credit" is VERY TRUE. If you do not think you have correctly satisfied the extra credit on assignment 6, then just do not attempt it. Each assignment took approximately this much time to complete: 1. survey - less than 30 min 2. git - around 2 hours (the assignment has some tricky wording, so I had to re-do part) 3. java programming - 4-6 hours 4. simple Android app - 6-8 hours, most of my time was spent trying to compile correctly because my Android Studio version was newer than what the assignment supported. 5. UML diagram - 5-7 hours. 6. testing - 8-10 hours Group Project: I luckily got a very good team. I think it is partly because I had no experience as a software engineer, so all of my teammates were software engineers. We communicated regularly on a private Discord group and were able to split the workload evenly amongst everyone. Despite not having past work experience as a SWE, I have written code in my current job and have a BS in Computer Science, so I was able to contribute a good amount to the team. We finished each deliverable well before the deadline. I can see how having a bad group would significantly impact your enjoyment of this class. I feel very lucky to have had a group much better than any I had in undergrad group projects. Individual Project: There are 4 deliverables, one due each week. They each take a vastly different amount of time to complete, with some requiring a lot of work and others being very easy. I don't think I can give away specifics of what each deliverable includes, so without any descriptions of the instructions, here is approximately how long I worked on each portion: 1. 16 hours 2. 15 minutes to get 100%. Then another 2-3 hours attempting the extra credit (which I did not manage to complete). 3. 5-8 hours 4. 30 minutes Participation: In addition to the coursework mentioned above, there is also a group participation/collaboration grade (10%) and overall class participation grade (3%). My group participation grade was 99% despite all teammates agreeing that we each pulled our weight in the project. I saw another reviewer suggest that the TAs may have a hidden set of criteria they use to finalize your collaboration score - I'm not sure if this is true or not though. My overall class participation grade was 100% despite not participating on EdStem much. I was very annoyed at the spammy students who would 'participate' by chaining 20+ "Thank you"s at the end of someone else's post. I did not do any of that and only participated when I had something legitimate to ask, answer, or share that would contribute to the conversation and still earned a 100% grade for participation. Overall: I felt that the effort required to earn a high grade was low. Not much coding was required, and the code that was assigned was mostly trivial. In this class, I learned a lot more about the documentation developed in the process of creating large pieces of software, but I wish there were more assignments about these pieces of documentation since that was my main takeaway from the class. The only time we wrote documentation for an assignment was the group project, but it was split among various group members. I would have liked more of the documentation to be done individually. Rating: 4 / 5Difficulty: 1 / 5Workload: 8 hours / week - UPMquKZjOzk3B7vxhaaTkA== February 7, 2026 fall 2025 [Digital Marketing](https://www.omscentral.com/courses/digital-marketing/reviews) Really light workload, 5 hours a week is being generous. Class is well organized and they provide everything up front at the beginning, so you can theoretically finish the whole class in the first week. Only "difficulty" is the memorization required for the exams. I scored a C on the midterm, so for the final I made sure to create and memorize flashcards and be able to recite all of the terms from memory which got me an A on the final and thus the course. Outside of the exams, there are 5 case study responses where you ready a case study and analyze it and weekly discussion posts where you need to respond to their prompts and reply to someone else. If you're able to finish most of the coursework ahead of time you'll just need to make sure you respond to another classmate's discussion post to get full credit for that week. Also it's crazy that this needs to be said, but please create your own response for the posts instead of just using ChatGPT. Rating: 5 / 5Difficulty: 1 / 5Workload: 5 hours / week - rBAAprTd7n4xR3KjrheEEg== February 6, 2026 spring 2026 [Computer Networks](https://www.omscentral.com/courses/computer-networks/reviews) I came into this course with no formal experience in computer networking or network engineering since I needed a class for registration and the waitlist for the other courses didn't have much momentum. For me, I needed to play catch up in terms of assumed understanding of how subnet, NAT router, ports actually work to make sense of the modules. Content: - Pretty dense modules and you have to read carefully - Kurose book and the youtube channel are helpful if I get confused by the professor's explanation. There were a few times where I needed to reference Kurose book for a clearer explanation Projects: - Required an intermediate level of knowledge with Python. Should not be too bad compared to other classes like DL from an "amount of coding perspective" - If you leverage the resources provided and READ the specifications BEFORE diving into the code, you should be able to get full score on Gradescope Community: - The TAs are pretty available on Edstem. There are dedicated TAs for the programming projects, content Q/A and general office hours - For the projects, the TAs provide chat sessions where you can ask questions about the projects. I found going to these really helpful in coming up with a simple, sufficient approach for the project implementation. Also, the chat sessions are very underutilized, so you should attend these when the projects come out to get the most support. - The wider office hours from the head TA aren't really productive. It's just more of administriva and very limited questions are asked - Professor Konte releases module summary videos which help to identify what are the main takeaways from the module. I didn't see too much of Professor Konte in the live setting so far Some areas of improvement: - Please update the documentation for how to setup mininet. Turns out the documentation provided in the Ed megathread was not accurate for Mac ARM processor devices. It would be nice to have a step by step video that's updated - The head TA doesn't really seem to answer a lot of questions. There are times where I asked a legit question in office hours and the head TA "shoots down the question". If you're gonna be helpful, at least answer the question or point in the right direction (eg: linking the edstem thread). Don't just answer every question with "that was clarified earlier". Most of the program consists of working professionals that also have lives - That being said, the project TAs and the content specific TAs are pretty good and clarify the doubts - Lower the weight of individual exams and increase the weight of the projects Rating: 4 / 5Difficulty: 4 / 5Workload: 12 hours / week - Gf7SwPsU9UURrDrapklYOg== January 29, 2026 spring 2026 [Secure Computer Systems](https://www.omscentral.com/courses/secure-computer-systems/reviews) It's unfortunate that this course is so terrible because it covers the kind of topics that I'm really interested in. Just like a lot of other reviewers mentioned, the quiz questions are poorly-worded and in some cases just plain wrong. It makes me wonder if whoever wrote the questions even understands the material themselves. This course isn't graded on a curve because it's difficult; it's graded that way because it's impossible to get a good grade when the test materials are unintelligible. I have no idea how a course could have so many complaints over a span of years and still not get fixed. TL;DR - This course is still a dumpster fire and it does not appear that there has been any kind of attempt to fix it. Rating: 1 / 5Difficulty: 2 / 5Workload: 10 hours / week - Bm6WunrnUMOeGi0X98AbfA== January 29, 2026 fall 2025 [Introduction to Information Security](https://www.omscentral.com/courses/introduction-to-information-security/reviews) This was an incredible course and Dr Wenke Lee is awesome. This class is basically a big CTF that is challenging, but they provide so much guidance and help, so it is still tough but very doable. I learned so much in this course, and they put so much effort into the labs and course material. If you are interested in cybersecurity, I cannot recommend it enough\! Rating: 5 / 5Difficulty: 3 / 5Workload: 10 hours / week - YJsqI0daonQZWcwuhRHNdA== January 27, 2026 fall 2025 [Artificial Intelligence](https://www.omscentral.com/courses/artificial-intelligence/reviews) Course has many interesting topics, TAs are helpful and this course has one of best TA support but everything else is made as confusing/hard as can be made. Each assignment has different number of gradescope submissions for no reason. Assignment 2 is not hard but you need an element of luck, that assignment works on gradescope for a small range of parameters. With limited attempts available, you have to be lucky to get it right even when your code is right. 6 attempts per 6 hours doesn't means 24 attempts in a day because most OMSCS students have job and need bare minimum sleep to survive. Basically, it translates to 6 attempts per day. Some other assignment instructions are made lengthy just because nothing should be straight forward. Focus in exams is on making them lengthy which leads to too many students seeking clarifications throughout the exam window. All this with MOOC level lectures. Overall, amongst most stressful courses in AI/ML specialization. Rating: 1 / 5Difficulty: 5 / 5Workload: 25 hours / week - UmpoA1qvCf95whP2KKtuNQ== January 25, 2026 fall 2025 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) For context this was my first course in OMSCS, and I come from a non CS background. However I have been working as a Software Engineer for 1.5 years when I started. I finished this class with an A. Pros: - Very very well organized class - Lecture videos are good quality - Projects were well put together, with clear instructions. Also felt like they did add to the learning. - Exams were fair Cons: - Don't get fooled by the mid-semester lull, where there's not much going on. Use it to study even harder for the finals. - Papers and some of the examples are based on older systems, might've been nice to explore the newer stuff. Rating: 5 / 5Difficulty: 3 / 5Workload: 16 hours / week - wWrNs/uhatb6su3iGfThYQ== January 25, 2026 fall 2025 [Introduction to Computer Vision](https://www.omscentral.com/courses/introduction-to-computer-vision/reviews) This course does a good job of exposing you to the fundamentals of CV. It’s not teaching you the latest techniques, but giving you the foundations on which they were built. I think it was a very good introduction class. It was my first class in omscs, so I did not really know what to expect. The assignments being due every 2 weeks ended up functionally meaning I would relax one weekend, then cram as much in the next weekend as I could. I found each assignment took me 15-20 hours on average, with the first one being easiest. The final project took me a very long time to complete, and I did not sleep much for two weeks while working on it. But, it was graded fairly. And the final exam was very easy - multiple choice, open note, open internet. I came into the class with experience working in python, and have used some opencv at work, but was still mostly reliant on LLM assistance for that. I come out of the class with a good foundation, I am glad I took it, and glad I wrestled with the material without relying on LLM code. Rating: 4 / 5Difficulty: 4 / 5Workload: 10 hours / week - KFCJslwPK2AlwJx/yRczvw== January 23, 2026 fall 2025 [Introduction to Analytics Modeling](https://www.omscentral.com/courses/introduction-to-analytics-modeling/reviews) TL; DR for ISYE 6501: Interesting lecture material + homework (15%) and project (8%) with work potentially sabotaged by peer grading. Horrible exams (75%). Some of the exam questions were so oddly worded that if English was not your native language you were at a distinct disadvantage. Enrollment: 1300+ students! Class subject matter+ HW assignments + project: 5/5 Peer grading and exams: 1/5 Overall course rating: 3/5. Exams and peer grading are red flags. Grades: HW + Project 100, Exams (average) 87, Final grade A (90%) Pros (Top 3): 1. Excellent choice of topics and covered in just enough detail by Dr. Sokol in well-organized lectures. 2. Interesting homework assignments, designed with the lectures in mind. HW consists of 80% of your time in this class and where you will put work in. This course needs to use the auto-grader for the coding. 3. The project assignment allows a deep dive into a particular problem and requires you use at least three of the methods acquired in the first 10 weeks. As with the homework you get out of the project what you put in. Cons (Bottom 3): 1. Exams: 75% of Grade. It’s a shame that the often ambiguous and poorly worded exams account for 75% of the grade in this course. Many exam questions introduce an unnecessary level of ambiguity that is unsettling. 2. HW: Homework and Project (23% of Grade) are all peer graded, and account for almost a quarter of the grade. Some of the peer reviews I received were performed with only a modicum of effort if any. Given the quality of gatech.edu as an engineering school, the lack of an auto-grader for coding exercises is unforgivable. 3. Office Hours (OH): Due to work pressures I had to finish the HW well before OH on Monday. So, OH were not very useful. As reported in OMS reviews, some students waited for the office hours the Monday before the HW was due and then copied the work done there. Some of the HW rubrics were weak and nearly incomplete. Six course design fixes that would allow ISYE 6501 to achieve a 5/5 rating: 1. Exams: Make exams better reflect the material not the ability to dissect triple negatives and split infinitives. 2. Grading: Please reward work on homework writeups. At minimum a 50%-50% split between HW/Project and Exams. 3. Coding: Include a 5-10-minute TA-led segment demonstrating R or python code relevant to HW as part of the lecture. 4. HW: Implementation should require the student to deep dive the details. Provide more test problems. 5. Require 2+ of the HWs (chosen randomly) to have one TA grade to ensure quality grading & identify poor peer graders. 6. Get rid of Piazza, use Ed. Rating: 3 / 5Difficulty: 3 / 5Workload: 15 hours / week - 5KFaeI5zlX6a7rXzBbKy1w== January 18, 2026 fall 2025 [Data Analytics and Security](https://www.omscentral.com/courses/data-analytics-and-security/reviews) I received an A in the course, however it is an extremely badly organized course by the professor and especially the head TA. The course content is also just basic statistics and an intro to Python and R course. Assignment and project instructions are extremely vague, rubrics that are given are not the standards that the TAs mark with according to both the professor and the TAs. According to the head TA Emma Kathryn Shumway, she's been working as a TA for this course for 10 semesters. The course still being this badly organized with the exact same problems that other reviews have discussed years ago shows that the problem is with the professor as well as whoever is leading the TAs (probably the head TA). The head TA also deducts marks for things that she said was acceptable on Ed discussion, and when brought up she refuses to adjust marks accordingly. When asking private questions on Ed discussion about projects and assignments, myself and multiple other people that I've talked to have been ignored. The professor, Dr. Borowitz seems nice during office hours, but over the semester I sent him 3 emails regarding assignments or projects and he did not respond to a single email. Overall I have to say this course is the least organized and the most frustrating course I've taken at Georgia Tech. Rating: 1 / 5Difficulty: 2 / 5Workload: 8 hours / week - zTGtCcoUrbslUl/F5gCtgg== January 17, 2026 spring 2026 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) Spring 2025. Way more time consuming than it is worth imo. Really good lecture. Shit load of busy work. Do not walk into this expecting an easy class. Low brain power? Yes. Multiple things to do every week? Also yes. If the entire course was like the first half that would be great, but once the lectures stopped the course kinda went downhill. Less busy work and this course would be awesome. If this is the only course you are taking, then 5/5 great class. I just found it stressful to handle so much extra work because I was taking 2 classes this semester. Rating: 2 / 5Difficulty: 2 / 5Workload: 15 hours / week - zTGtCcoUrbslUl/F5gCtgg== January 17, 2026 fall 2025 [Deep Learning](https://www.omscentral.com/courses/deep-learning/reviews) I was so burnt out taking this course. Please do not double up on this one. Somehow got an A at the end, but did not learn as much as I wanted because I was so tired by the end. Covers an insane amount of content. Grading largely via auto-grader so not as vague as something like ML. However, performance is a portion of your grade (do not take this class if you dont have a GPU), and there is honestly not very much room to really experiment with ideas because everything is so clearly laid out in the autograder. You will know that a lot of things EXIST, but not actually understand them. Regardless, a good survey course for that. You will be forced to learn a lot, just not that deeply imo. There is a group project. It is graded very easily. Honestly you can probably get an A on this doing a solo project if you needed to. Pick something interesting and don't worry about getting good results. Find team-members early. Pro Tip: Give up on the quizzes, the ROI studying for them is not there. You should be getting an A on every assignment if you just put in the work. If you put in the hours you WILL do well. I spent significantly more time on this course than ML (took over the summer) on a per-week basis. Rating: 4 / 5Difficulty: 5 / 5Workload: 20 hours / week - zTGtCcoUrbslUl/F5gCtgg== January 17, 2026 summer 2025 [Machine Learning](https://www.omscentral.com/courses/machine-learning/reviews) Amazing course. Time consuming. Great 'professional DS' simulation if you are interested in that career. Don't overthink the assignments. I spend way longer on the first few, but didnt really get a better grade. Try to timebox to 20 hours - 30 or 40 at the absolute max. Try to start at least the weekend before they are due (2 full weekends to work on the project). Rating: 5 / 5Difficulty: 3 / 5Workload: 18 hours / week - zTGtCcoUrbslUl/F5gCtgg== January 17, 2026 spring 2026 [Applied Cryptography](https://www.omscentral.com/courses/applied-cryptography/reviews) Taken Spring 2025. I studied math in undergrad. Made this a lot easier. Would be a 5/5 except the TA and grading is honestly a pita. It is extremely unclear and thier definition of a 'proof' and what can and cannot be assumed is very misguided tbh. A lot of the problems are left extremely vague and you arent allowed to ask questions, but you are punished for making the 'wrong' assumption. I literally wrote down 2 possible solutions based on 2 different assumption sets for a vauge problem, and was marked down on BOTH solutions (one was 'incorrect assumptions' and the other had a small syntax mistake). This completely defeats the point of a proof based assignment - you should be assessing the logical reasoning and deductions not weather we can guess what you want for a given problem? No cryptography background needed for this course. This course was not exceptional but not bad either. If you want to learn how to do proofs this, albiet not the best avenue, is probably your best shot in this program. Rating: 4 / 5Difficulty: 3 / 5Workload: 10 hours / week - QXVJyKsMsSwQ8RZ4khjCCw== January 16, 2026 fall 2025 [Knowledge-Based AI](https://www.omscentral.com/courses/knowledge-based-ai/reviews) I don't really get all the complaints about this course. Some on reddit said "this is the worse class ever" while others on discord were saying that it was BS...uh...were we taking the same class? I guess one valid complaint is that the lessons aren't very applicable to industry, but like, that describes 70% of the content in this master's degree (except for GIOS, that class was amazing). I thought the class was pretty decent, even good at times, actually. Like sure, it's a David Joyner class so it will have a fair bit around of busy work but overall expectations were very fair and the homeworks and projects were pretty relevant and reasonable. I thought the course was altogether quite easy especially compared to summer ML4T and the TAs were very helpful. I wasn't a big fan of the lectures but some of the projects were fun and relevant. I personally reused my decision tree code from ML4T for one of the miniprojects and you got introductions into important algorithms like A\*, DFS, BFS if you chose to use them for the miniprojects. The new ARC-AGI project was also pretty fun and while some say it was harder than the old raven's projects, I thought it was very reasonable so long as you don't procrastinate. One key thing to note is that you get points for the training problems too, so literally you are guaranteed at least 50% of the code portion of the points if you aren't lazy. Some complained about the TA grading but I didn't have any issues and got literally a 100% for every written assignment I submitted. All I did was open the rubric (there should be a table rubric for each assignment) and I wrote to the rubric. Put my subtitles in my paper as the exact same row name in the rubric and wrote to the rubric, and I never had a problem with grading. Heck, I thought the grading was more lenient than most of my undergraduate classes. Seriously y'all. Were we even taking the same class? Overall, 10 to 15 hours a week for this class as long as you are consistent. Pretty moderately easy. I think hardest parts were a few of the mini-projects and milestone D of the ARC-AGI projects, but if you do well enough on the mini-projects you can afford to half-heartedly address milestone D. Rating: 4 / 5Difficulty: 2 / 5Workload: 15 hours / week - \+P2SNPgxTxx8N5phkJLrpA== January 16, 2026 fall 2025 [Knowledge-Based AI](https://www.omscentral.com/courses/knowledge-based-ai/reviews) This course was my first OMSCS class. I came away with mostly positive feelings about the class. For starters - Dr. Joyner and the TA we excellent. They were super responsive, engaged, and enthusiastic. I think that the decision to migrate the semester project to ARC-AGI from Raven's Progressive Matrices was awesome. I appreciate how much work that must have taken - and I feel that it greatly enhanced the learning experience. Another positive aspect of the course is how well organized it is. It is clear from Day 1 exactly what you need to be successful in the class. Everything is available from the jump and this would be a great class to work ahead in if you wanted to. There are many assignments throughout the semester. While this can be a bit grating, or feel like busywork at times, they were generally interesting. And opportunities for easy points. Sometimes other reviews for other courses discuss being annoyed with the uncertainty - and I feel like this class is the antithesis of that. The lectures I found interesting at times. Unfortunately, they didn't feel as "rigorous" as I wanted them to. I feel like there are more abstract topics in computer science (like algorithms) are theoretically/mathematically well founded. Or there are more practical classes (like Operating Systems) which are grounded in their practical application in the real world. KBAI feels like a course discussing a particular view of artificial intelligence which is neither mathematically "true" nor broadly in use. It is a very "vibey" class which kinda left me feeling like I was not learning a "real" computer science topic. Some people in the class complained about the peer review software or some of the other administration of the class - but that never felt like an issue to me. Also - people who were complaining about not getting perfect scores on the assignments seemed to be missing the forest (an A is extremely attainable in this course) through the trees (missing 5% due to poor formatting on a report without comprehensive enough TA explanations). In summary - I think this is one of the best ran classes I have ever taken. It really does not waste your time teaching you the material along the way. Ultimately - the subject matter / topic did not completely resonant with me. Which colors my rating + feelings of the class. But depending on what you want out of it - it could be a perfect class. Rating: 4 / 5Difficulty: 3 / 5Workload: 8 hours / week - dOsCVsfzgP02nQrTuuIGGA== January 14, 2026 fall 2025 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) excellent course\! Rating: 5 / 5Difficulty: 5 / 5Workload: 25 hours / week - cGGo8T2m8PqYVhqrIFO1ZA== January 14, 2026 fall 2025 [Database System Implementation](https://www.omscentral.com/courses/database-system-implementation/reviews) Lectures were useful maybe 50% of the time. Spent way too much time on c++ and not enough time digging into more internals of databases. I might just be too smooth brained, but I thought the exams were kinda challenging. Wording was strange at times, and I felt they took "practical application of course material, multiple choice, and not much written math" to its limit in difficulty. Some exam questions were on research papers that were provided throughout the semester. I found the topics interesting, but the reading load on them wasn't very balanced. TAs were slow to respond. Office hours were exactly once, 1 hr/week, which was bad, but always with the professor. The professor himself was one of the best parts of the class. Even though the lecture content was often not what I wanted to be watching, he's extremely happy to be talking about this material. During office hours, he was genuinely interested in hearing from students, helping where he could, and giving high-level overviews of the research papers. Rating: 3 / 5Difficulty: 3 / 5Workload: 8 hours / week - rBAAprTd7n4xR3KjrheEEg== January 13, 2026 fall 2025 [Data and Visual Analytics](https://www.omscentral.com/courses/data-and-visual-analytics/reviews) Pros: 1. Most of your grade is based on homeworks and team project so you're rewarded for the hands-on part of the course 2. Bonus quiz opportunities are there and pretty manageable if you are on the border 3. Unlimited Gradescope submissions for HWs, so you should easily be able to get majority of the points 4. Not too difficult as someone who has full stack software engineering experience Cons: Oh boy, there are plenty of cons\! 1. Team project experience was ok. I lucked out with getting a team where everyone contributed so peer evals were easy. I wanted to do an interesting project that wasn't some cookie cutter ML model thing, but the time constraint given from the course was limiting. My team initially operated with 1 month worth of time for the project, but due to HW 4 and the annoying reports to write, there was really 2 weeks of time towards building the project. Splitting the work helps, but still we had to pare down a lot of the scope and the final product was kinda lackluster. I recommend picking up Streamlit and the documentation is very good 1. HW 2 (the D3 one) was kinda annoying. The D3 library is very finicky to pick up and you had to match the exact HTML structure to the T in order to get the autograder points. I had scenarios where the D3 visualization was bad but passed the autograder. 2. Lack of opportunity to assess visualizations we create. For a course that's about data visualization and analytics, that piece wasn't really covered. How about add a section or multiple choice piece in gradescope where we have to write a few sentences about how an existing visualization can be improved based on the provided context 3. Professor was hardly present in the course. I'd like to see a little bit more of Polo in the picture Rating: 3 / 5Difficulty: 2 / 5Workload: 10 hours / week - 9uYS8I6w+YWG6eX6KLPahQ== January 13, 2026 fall 2025 [Special Topics: Global Entrepreneurship](https://www.omscentral.com/courses/special-topics-global-entrepreneurship/reviews) This was very helpful for those especially wanting to make a start up. The lectures are practical and the assignment is a semester long mock start up. I agree with the professor, the only way to learn business is to do business and this mock start up is exactly how to go about on making a business. It's great to pair up this class with another. Rating: 5 / 5Difficulty: 1 / 5Workload: 5 hours / week - fVbu3miGRDfqMltO4NgwHA== January 12, 2026 fall 2025 [Mobile and Ubiquitous Computing](https://www.omscentral.com/courses/mobile-and-ubiquitous-computing/reviews) Pros: ``` The content is interesting The lectures are really valid from a content perspective TAs are supportive most of the time Teachers are supportive and welcoming during office hours The quizzes are "ok". Some of the questions are "confusing", but I wouldn't complain too much about that. ``` Cons: The course is badly organized. There's little room to plan ahead. The course will be unlocked after the first week. On Canvas you'll see everything due for December 1st, however the real deadlines are different. This might cause some confusion. There are neither notes/written versions of the lectures, nor you can download the videos; usually I wouldn't complain, however I want to mention that on Canvas the video player is awfully small. Not sure if this is an issue for most of the people, it was for me. Individual assignments and Group Project are the worst part: There are two individual assignments. I won't share too much detail on the assignment itself, but I want to complain about the way it's proposed. We were given the assignment description and a template. The real issue is that the assignment description and the template differ on some points. Clearly one of the two wasn't updated but they still expected you to follow both, since the grading of the paper really depends from it. Let me give you an example without giving too much detail about the assignment itself. ``` Assignment description: go from A to B and print the number of seconds you took to go from A to B. Print the value on a chart. Then go from point B to point A walking backwards. Template description: go from point A to point B. Then print the result, then print the chart. Then repeat the steps, print the value, print the chart. Compare the two charts. Grading description (available only when the TAs evaluate your submission) will loosely match the template description, but not at 100%. ``` However, following both points is confusing, especially because the assignments description don't match at 100% and TAs have to give extra information, for example by saying which task has to be excluded from the submission. Why couldn't they just write an assignment that includes everything? Unexpectedly, the second assignment is incredibly well written and the requirements are clear. If you already took HCI, there's a lot of overlap with some core concepts and, in my opinion, most of that content is better covered by Dr. Joyner's class, at least from an organization and material standpoint. I understand that some people might be interested in taking this course rather than HCI, but I have to consider that this is a core course for the HCI specialization, so the overlap is almost certain in case you enrolled in this specialization. The poor course organization reflects into parts of assignments being postponed and/or canceled. Is not a bad thing, but it really gives you little room for planning ahead. There are few mismatches between Canvas grades and what's written on the syllabus, this is not really clear, my team and I might just be wrong, but it appears so. Up until now is the worst course I've taken. I don't know if I've been spoiled by the quality of previous classes, especially Dr. Joyner's, but is a fair course that's make awful by the lack of organization. Teachers and TAs try to make up for this by being really flexible and supportive, but wouldn't it be just simpler to reorganize the course for good? TL;DR Version Interesting content and solid lectures, with supportive instructors and TAs. However, the course is very poorly organized. Deadlines are unclear, materials don’t match (assignment descriptions vs templates vs grading), and planning ahead is nearly impossible. There are no written notes, the video player is tiny, and some quiz questions are confusing, not to increase the difficulty of the course, just badly written. Individual assignments and the group project suffer the most from inconsistencies and last-minute changes. Compared to other classes, the overall structure and clarity are significantly weaker. Instructors try to compensate with flexibility, but the course urgently needs a proper reorganization. Rating: 1 / 5Difficulty: 1 / 5Workload: 10 hours / week - sopEmb90N5ucEVVYW1g0wQ== January 12, 2026 fall 2025 [Deterministic Optimization](https://www.omscentral.com/courses/deterministic-optimization/reviews) I thought this was an excellent course. Even coming in with industry experience in mathematical optimization (LP/IP, commercial solvers), I learned a lot of genuinely new and useful material. The only real downside is the timing around the midterm—having a regular homework due during the main exam study week can be rough. Overall impression I genuinely think this is a great course. It’s well-structured, the topics are thoughtfully sequenced, and the class provides a strong foundation that is both academically solid and highly relevant to real-world optimization work. For context, I finished the course with an A. My background (so you can calibrate this review) I work professionally as a mathematical optimization / operations research engineer. In my day-to-day job, I build optimization models and solve them using commercial solvers such as Gurobi and IBM ILOG CPLEX. Before taking this class, I already had a working knowledge of linear programming and integer programming, so I did not start from zero. What I liked most: topic coverage and progression One of the best parts of this course is that it feels like it walks through the “standard” optimization curriculum in a clean and logical order—very similar to how a good optimization textbook would build up concepts from fundamentals. That said, even with my background, I still found a lot of value because the course includes advanced (but very practical) topics that I had not studied deeply before. Examples include: • Transforming certain robust optimization formulations via duality (and seeing how they can reduce to more standard planning formulations) • Dantzig–Wolfe decomposition and the underlying idea of decomposing large structured problems • Actually getting hands-on exposure to column generation, which I strongly believe will translate directly to real industry projects Nonlinear / convex optimization coverage I also appreciated that the course doesn’t stop at LP/IP. It introduces the “entrance” to nonlinear optimization and convex optimization in a way that’s approachable and easy to follow. It won’t turn you into a convex optimization specialist overnight, but it does a great job giving you the core intuition and vocabulary. One thing I would improve: midterm week load If I had one critique, it’s the scheduling around the midterm. During the key week when you realistically need time to study for the midterm, you may still have a normal weekly homework due. That alone is tough, but what made it harder for me was that the homework around that time covered concepts that become very important later in the course. If your understanding gets shallow there due to time pressure, the second half can feel unnecessarily painful. So I don’t think the homework itself is “bad”—it’s important. I just think the overlap of heavy exam preparation + regular homework in the same week is a bit brutal and could be adjusted. Exams, pressure, and whether you should take it This course is definitely motivating: it pushes you to study seriously, and an A from this class really does mean you put in the work. Personally, I actually liked that aspect. In my case, I scored around 80% on the midterm, which put me under pressure to perform extremely well on the final. I ended up getting a perfect score on the final, and the process of studying under that pressure honestly strengthened my understanding a lot. So here’s how I’d frame it: • If you want an “easy A with minimal stress,” you might want to avoid taking this in a term when your schedule is tight. • But if you’re okay with a normal level of graduate-school intensity—and you want a rigorous, valuable optimization course—then I’d absolutely recommend it. Rating: 5 / 5Difficulty: 4 / 5Workload: 15 hours / week - SpcHYLG1mx3cm3W562UheQ== January 10, 2026 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) I thought that this was a great course that's very applicable to industry. The content was very interesting, even though it wasn't a technical course. The best part about this class were the lectures, as they were so well made. The readings were super interesting as well. There are three phases of this class: 1. The content phase: this is where you watch the lectures and complete 4 homework assignments, which are papers you have to write by answering four questions. 2. The practice phase: this is where you do the readings, complete quizzes on the lectures and the readings, complete test 1, and do the individual project. 3. The application phase: this is where you complete the team project and complete test 2. All in all, great course, although I missed learning more technical knowledge. Rating: 5 / 5Difficulty: 2 / 5Workload: 10 hours / week - yeBZMH1eU457toXtayf1WQ== January 8, 2026 fall 2025 [High-Performance Computer Architecture](https://www.omscentral.com/courses/high-performance-computer-architecture/reviews) I have no background in computer architecture not a computer science degree. I have exposure to OS and have been a professional SWE for 5 years. I found I had to catch up lots of hardware related topics that increased my weekly workload to 20 hours/week. Otherwise, it could be 10-15 hours/week. The material is great. Top notch, equal to the CMU course on YouTube. However, and I cannot stress this enough, THE PROJECTS SUCK\! You spend 5-10 hours tweaking parameters and recording perf. The end result is learning something obvious like "more cores = more overhead" or that "out of order execution order saves time". Really obvious information from the lecture that doesn't need repetition. I would have LOVED to implement some hardcore structures like writing a cache coherence simulation or coding reorder buffer logic. The most coding is ~50 lines of code to write LRU cache. This is a basic leetcode question. Not okay. I expected better. The course seriously needs a revamp here. I hope the professor reads this. Rating: 3 / 5Difficulty: 4 / 5Workload: 20 hours / week - kPRbSxTFjIkenr0EYxqjcQ== January 8, 2026 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) This course has a great professor who has a passion for the subject. Course was organized pretty well. There are two large projects broken up into small parts to make them digestible. The second project is a repeat of the first but in a group setting, which I didn't find valuable. The assignments are all written assignments (no coding). Rating: 4 / 5Difficulty: 3 / 5Workload: 11 hours / week - 7o5/Qgul8567CvjdgPz0Qg== January 8, 2026 fall 2025 [AI, Ethics, and Society](https://www.omscentral.com/courses/ai-ethics-and-society/reviews) This course is a good introduction to explainability and fairness in ML/AI. It is named the same as a conference called the AAAI/ACM conference on AIES which specializes on the same topic this course teaches. There is also a journal that publishes proceedings of the conference. I mention this because it gives students insight into exactly what you're signing up for. This is not a computer ethics class nor an AI ethics class in the pure sense. The "society" part is important because it takes a sociological lens and fairness here is understood in terms of bias against social groups. So once we understand the purpose of the class the material all makes sense. I docked a star because some of the assignments felt tedious, but I acknowledge it's hard to test for knowledge without some repetitive tasks. This is a highly important subject that is understudied and rarely used in industry but definitely necessary. Rating: 4 / 5Difficulty: 3 / 5Workload: 7 hours / week - 67SytxTnAw+4x2y4ZT4gvg== January 8, 2026 spring 2025 [Special Topics: Compilers - Theory and Practice](https://www.omscentral.com/courses/special-topics-compilers-theory-and-practice/reviews) This course was by far the most challenging I've taken so far at OMSCS. I came in with decent antlr knowledge from work experience .... I can only imagine what someone coming without that felt like. The final phase of the project was pretty brutal, I started early but still came down to the end. If you do not start early, you will certainly fail, the amount of hours to design/implement a solution is steep. You also often need to significantly refactor previous iterations of the project to accomplish the next step I found, which ate up a bunch of time. Rating: 4 / 5Difficulty: 5 / 5Workload: 25 hours / week - Fk0FQSMCiLF4JSvmuaGBhg== January 8, 2026 fall 2025 [Quantum Computing](https://www.omscentral.com/courses/quantum-computing/reviews) This class was really nice and interesting imo. I suggest it. Two exams, 4 labs, the exams are proctored which is annoying but I get why. Very informative class. Rating: 5 / 5Difficulty: 4 / 5Workload: 8 hours / week - QJfnPoFqMua2oeZuSZNI1g== January 7, 2026 fall 2025 [Computer Networks](https://www.omscentral.com/courses/computer-networks/reviews) I learned quite a lot from this course, mainly from reading the textbook and doing the projects. The lectures are fairly boring for many of them, especially when half of them are just paraphrased passages from the textbook. I strongly recommend reading the textbook, it goes a bit more in-depth and helps you understand all of the required materials. The quizzes are easy as long as you have a good understanding of what you just learned. The assignments aren't that bad, I finished them in half a day each project. The exams are completely fair. The professor is mostly missing the entire semester which is unfortunate but, it is what it is. Overall, good course, but lectures could be improved. Rating: 4 / 5Difficulty: 2 / 5Workload: 4 hours / week - QJfnPoFqMua2oeZuSZNI1g== January 7, 2026 fall 2025 [Deep Learning](https://www.omscentral.com/courses/deep-learning/reviews) This course taught me a lot about Deep Learning. Some of the lectures could be better and the Meta lectures are mostly awful; however, self teaching through other materials such as StatQuest or Stanford lectures are very useful. Do not bother reading the textbook, it is absurdly in-depth and is not useful. The quizzes can be studied for using the study guides the course staff releases, but even then, some of the questions on the quiz just make you go "what???". The projects are very interesting but can be pretty brutal. Good course. Rating: 5 / 5Difficulty: 5 / 5Workload: 25 hours / week - gJxd5E3NulatPmx8Q9V2AA== January 7, 2026 spring 2025 [Big Data Analytics for Healthcare](https://www.omscentral.com/courses/big-data-analytics-for-healthcare/reviews) Great class overall to take near the end of the ML spec. The final project is very well thought out with topics given to us to choose from rather than us cooking up topics. The final project is done in duos so its not that bad and it can be as hard as you want it to be. I learnt a lot building and training a model from scratch for the final project. The exam is easy if you go through the lectures. Rating: 5 / 5Difficulty: 4 / 5Workload: 15 hours / week - gJxd5E3NulatPmx8Q9V2AA== January 7, 2026 spring 2025 [Data and Visual Analytics](https://www.omscentral.com/courses/data-and-visual-analytics/reviews) Do not take this class. You will work in a group of 5 to do a project that one person can do in the Ai era. Although you will learn a bit about full stack dev and Apis and learning how to learn random things quickly. Rating: 3 / 5Difficulty: 3 / 5Workload: 12 hours / week - gJxd5E3NulatPmx8Q9V2AA== January 7, 2026 spring 2025 [Database Systems Concepts and Design](https://www.omscentral.com/courses/database-systems-concepts-and-design/reviews) One of the most useful courses in OMS that you can take. It will take a lot of teamwork to get through the project's early stages so be prepared. One of the TAs is great, responds within the hour to any questions you ask. Rating: 5 / 5Difficulty: 3 / 5Workload: 12 hours / week - XWsfAaR0RRg6WjjxRoF0Dg== January 5, 2026 fall 2025 [Introduction to Information Security](https://www.omscentral.com/courses/introduction-to-information-security/reviews) Coming into this course its important to understand 1) It is run by TAs 2) it is project based. The other reviews state this as well, so it should not be a surprise. It may definitely have been nice to have the professor more involved, and high-quality lectures related to the course content would have been amazing, but that is not part of the course. The projects in the class are structured as a CTF style assignemnt - for the most part, you are working to identify flags hidden in an application. You will need to download a VM for this, so give yourself time to troubleshoot that if needed. The projects are each created and run by teams of 2-4 TAs (easier projects have 2, others have more). There may be more TAs in the background, but I only interacted with 2-4 on ed discussion/office hours. For about 60% of the projects (including the hardest ones), the TA who did the bulk of the work creating the project has long left the position. My general gripes with the course - 1. The TAs are inconsistent - on one project, you may be actively corresponding with the TA who designed and built it, while on others, you are talking to TAs who are more "maintainers." 2. The quality of TAs - almost none of the TAs actually work in a cybersecurity role professionally - a lot of them are simply folks who took and completed the course previously. Some of them have been a TA for quite some time as well. A recurring theme, though, is that these TAs often have no professional cybersecurity experience, and cannot help/teach further than the projects. Most of these teams no longer have the creator of the project around, so a lot of answers to questions are "just figure it out" or "use your resources." It is pretty clear after the course that a lot of the TA's knowledge of cybersecurity does not go past what is taught in the course and is very surface-level. 3. Ed discussion moderation - as the 1 - 2 weeks you have for each project goes on, you notice TAs remove/redact less and less from posts (as the volume of posts naturally goes up). If I had just waited until closer to the deadline on a few projects, the answer is pretty clearly written on ed discussion. You can find details on individual projects in the other reviews and I generally agree with those. The course heads really need to take a look at the overlap between projects (half of malware analysis just felt like the web exploitation project) and the usefulness of some projects (Machine learning was a complete waste of time). Many of the projects are at least 3-4 years old and may not be as relevant (the log4j project, while interesting, was little more than a wrapper around a hackthebox lab). Rating: 2 / 5Difficulty: 1 / 5Workload: 12 hours / week - oEQOXEftcE6DcQclBrWoWw== January 5, 2026 fall 2025 [Distributed Computing](https://www.omscentral.com/courses/distributed-computing/reviews) To be honest, getting B on the course might be easy since getting 62% overall alr gives you that. About the latest review prior to mine, i don't think that the last project only costed 15 hours and you alr got 82%. I spend more than 50 hours, code hundreds to a thousand LOC and only got 72%, given that too many edge cases for different parts that were not initially accounting for, hence may need to redo certain parts. I have 4 years of experience in backend development with Spring, solve a thousand of leetcode problem in java, hence my coding ability in java with the Collection framework is not at the beginner level. Mid-term and Exam-wise, I think that it depends, you can still study hard but unfortunately get low grade since you may focus on slides, lecture videos while the exam questions focus on the original papers. In my opinion, you still can get A if you do the bare minimum for programing parts 3 and 4 which are the main culprits for student depression (5%/5% p0 + 10%/10% p1 + 8%/10% p2 + 5%/15% p3 + 5%/15% p4 = 33%/55%) while getting full marks for participation (5%/5%) and full mark for exam (40%/40%) since cut-off for A is 82%. Regarding the contents, i find the first half useful since it makes you reasoning things well and will sharp your mindset into thinking what failure models you may get into, what should be done to prevent that during your system design/technical discussion. The second-half is more about the case studies and does not leave much impression on me. Rating: 4 / 5Difficulty: 5 / 5Workload: 30 hours / week - r9dfALdlHDI51NbnofDZ3A== January 5, 2026 fall 2025 [Machine Learning](https://www.omscentral.com/courses/machine-learning/reviews) The concept of this course is interesting, but the execution is very flawed. Machine Learning focuses on the experimentation portion of machine learning. How do you interpret the results of a model? Is this model appropriate for this dataset? How do you verify a model's "correctness" for larger scale use? Unfortunately, the course itself isn't focused on teaching you how to go about doing those things. The reports that make up a bulk of the class work are entirely focused on interpreting and analyzing your experiment results. However, the class has no real introduction/lecture on the metrics that are commonly used or how to appropriately interpret models, leaving us to hopefully stumble into an effective teaching of these on our own. As of Fall 2025, we now have 10 - 20 page assignment docs - which provide *some* guidance into what metrics to look into by virtue of mentioning that a particular plot should be included, but even these aren't complete due to a lack of a formal rubric and additional instructions scattered on Ed. Only after the grades for A1 were out, and sample reports from other students were posted, did I get a better idea of what the "expected" interpretations/metrics were. This approach is certainly exploratory, but combined with the grading lottery others have mentioned, the lack of rubrics + scattered/unclear requirements, and the lack of guidance in appropriate exploration of a model... I found myself learning a lot less than I hoped, and instead spent most of my time guessing requirements and formatting LateX papers and plots to fit a strict page limit. Rating: 1 / 5Difficulty: 4 / 5Workload: 20 hours / week - ND4KfHYB+6idCR30DXEWWA== January 5, 2026 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) Marked the workload at 6 hr/wk but that's on average. There were weeks I spent 10 hours, and weeks I spent less than 3. I took this as my first OMSCS course because I heard it was well-structured and a good 'medium' difficulty entry point for graduate level classes. I agree with that. There's a detailed course calendar and all lectures and homework assignments are available at the beginning of the semester. The expectations for students are clearly laid out and I was able to work a week ahead, which helped a lot when stuff in my personal life got busier. I learned a lot and found the subject material super interesting. There's a lot of reading, so if you're a slow reader you may want to budget more time. The group project is kind of a waste of time (it's just the exact same thing as the individual project, but in a group), but I found a good group early and we did the project without any issues. The way the course is structured, you have to learn everything, do homework, take 4 closed note quizzes, and do a solo project in the first 11 weeks of the class. This is the part of the course that took me 10 hrs/week. Then, the last 5 weeks of the course is only submitting check-ins for the group project and taking 1 (open note) test. Since I had a good group, it took me 3 hours a week max to do the work required for the group project. Rating: 4 / 5Difficulty: 2 / 5Workload: 6 hours / week - GvorwXgJMs6F7hAO5LvZjg== January 4, 2026 spring 2025 [Introduction to Information Security](https://www.omscentral.com/courses/introduction-to-information-security/reviews) I achieved a solid A in this class and skipped doing the last assignment. Pros: Some fascinating topics. You learn quite a bit about foundational programming and computing topics. Things you are guaranteed to never use in your job, but you feel more accomplished knowing them, and are more well-rounded. Cons: If you find solving puzzles completely exciting, and being unable to solve some puzzles frustrating, this course will frustrate you. There were 2-3 assignments I couldn't figure out the final answer to, no matter what I did. I am confident that one of them was likely a bug in the assignment, but the TAs ARE NOT ALLOWED to help you. You either solve it, or you don't. I cannot overstate, you need to go into this class expecting that no matter how intelligent or accomplished you are, you may not solve every puzzle; AND be okay with not knowing why. Ha. Rating: 3 / 5Difficulty: 4 / 5Workload: 8 hours / week - GvorwXgJMs6F7hAO5LvZjg== January 4, 2026 fall 2025 [Data Analytics and Security](https://www.omscentral.com/courses/data-analytics-and-security/reviews) I achieved a high A in this class. Pros: Subject matter and quizzes are straightforward and do not take much time. For half of the semester, you can complete your week's work in about 1-2 hours. The course is heavily weighted toward the final project and paper. If you work on that consistently and early, the course is a breeze. If you have no experience in data analytics, its a great foundational course to get your feet wet. Cons: Some of the TAs' grading does not demonstrate competence. I spent around 80 hours on the final project alone because I wanted to really blow it out of the water. Those 80 hours do not count my teammates' contributions. And we received a B on our final project because the TA "significantly" did not follow the grading rubric. I found that quite frustrating and un-academic. I professional brought it to the TA's and the Professor's attention, and received no response. Many people complained about the TAs grading on the mid-semester project, and I can see why. Takeaway, I find that this class is overly weighted toward a complex, many-faceted, final project (30 page paper + 20 minute presentation) that is too complex for TAs to grade correctly. Rating: 4 / 5Difficulty: 2 / 5Workload: 4 hours / week - UGUoDfisXh5NauhtIFsIUg== January 4, 2026 fall 2025 [Artificial Intelligence](https://www.omscentral.com/courses/artificial-intelligence/reviews) This is an exceptionally difficult class. For context: I likely have more experience with Python than the average OMSCS student, but less overall CS experience. I took several related classes to prepare me for this one (KBAI, Game AI, AI4R, etc.), and it was still rough. But how difficult you find each assignment greatly depends on your familiarity with each section, and what your natural aptitudes are. Additionally, part of the difficulty comes from the strict plagiarism policy, which limits the external resources you can consult. Here's a breakdown of each assignment: A1 - A\*. ~60 hours if you haven't taken a graduate-level class that teaches A\* at a high rigor, ~20-30 with. Expect extra time if you want a 90%+. It took me ~40, and I found it to be the easiest assignment both to conceptualize and to program, despite most students saying that it's by far the hardest. The time investment comes from implementation size rather than conceptual difficulty. A2 - Game playing. ~40h if you're not comfortable with recursion and debugging complex recursive algorithms, ~20h with. I had a terrible time with this assignment due to misinterpreting the provided documentation, but otherwise thought it was conceptually straightforward. A3 - Bayes nets. If your understanding of graduate-level stats is solid, this assignment can be done in 5-10 hours. Otherwise, you're in for a rough couple weeks. I spent ~30 hours prepping for the assignment, and another ~30 on the assignment itself. This assignment requires a tenth of the coding of assignment 1, but it was far more difficult for me. A4 - Machine learning. If you're comfortable with numpy and vectorization, ~20 hours, ~40 without. This was the first assignment I felt that the provided material was not enough to understand the concepts, so I had to do a lot of self study. A5 - Gaussian mixture models. This is a very polarizing assignment. The first half requires what I thought was incomprehensibly obtuse numpy broadcasting and spatial reasoning, and it was easily the worst experience I’ve had in any CS class due to a complete mismatch with my aptitudes. The second half is comparatively trivial and doable in an hour or two. If you have strong linear algebra skills and a good working spatial memory, this will likely be a breeze. Otherwise, expect ~50 hours on the first half alone. A6 - Hidden Markov models. I didn't do this assignment, but the folks that did said it was on par with the difficulty of assignment \#4. Difficulty: A5 \> A3 \>\> A4 \> A2 \> A1 Time taken: A5 \> A1 \> A3 \> A2 \> A4 The midterms and exams are a great way to review and solidify your understanding of the material. However, you aren't really graded on your understanding of the material, but rather on how well you can solve dozens of problems without any mechanical errors. Being off by one decimal after 2 pages of math is worth 0 points, as is taking the right approach but making a minor mistake along the way. In addition, there are several ambiguously-worded questions and later-corrected solutions, and I found it to be a stressful experience. There's a 24 hour challenge period after the exam ends where you can argue your case for why your incorrect answer should be marked as correct. Expect your grade to jump as much as 1-2 letter grades (yes, 10-20%) after regrading. I asked for clarifications on a couple questions but was denied due to exam policies, so I had to guess between two answers, and later learned I chose the wrong ones. But overall, I found the TAs to be pretty generous and forgiving with points. Effort expended on exams does not necessarily correlate with a higher grade. Don't beat yourself up if you test poorly, it doesn't correlate with how well you understand the material. Lecture quality and usefulness varies. Some lectures were too high level, and others were better grounded in examples. I strongly recommend reading the textbook. I fully read or skimmed ~1000 pages throughout the course. I didn't personally find the discord helpful. Due to the plagiarism policy, most students are hesitant to share any tips, so it's better for morale-checking rather than assignment help. I recommend sticking with EdStem. The TAs are responsive and usually helpful, but they're sometimes hesitant to share concrete tips. Office hours are generally one on one, and I recommend joining those if you have questions or need a code review. If you're looking to prepare for this class, I *strongly* recommend these three things: brush up on A\*, learn how to debug (setting breakpoints, stepping through the code, etc.), and learn how numpy broadcasting works in 1D, 2D, and 3D. Linear algebra and calculus would help too, but I didn't struggle on those portions. And lastly: this review comes off as intimidating, because that's how I felt throughout the whole of the course. Conversely, I know many folks in discord who thought everything was review and never struggled at all. If you put in the time, you can get through this course. Due to varying assignment difficulty, I spent 10-50 hours/week on this class. Rating: 3 / 5Difficulty: 5 / 5Workload: 35 hours / week - vsibVbdFfYHQ84sN6cGhvw== January 2, 2026 spring 2025 [Digital Health Equity](https://www.omscentral.com/courses/digital-health-equity/reviews) This class has been available to OMSCS students for a while now but has not been on omscentral for some reason so I'll happily write the first review. I'm only now seeing on omscentral but I took this course a few semesters ago so i might be a bit hazy on some of the details. Professor Parker is very knowledgeable in her subject field which made all the lectures easy to understand. She records the lectures herself, so they are well made and seem relatively up to date. This is more of a do your research and write papers type of course and is not code heavy at all. You are given weekly lectures and readings about health equity. You will mostly learn about disparities within healthcare and how technology can be used to fight those disparities through the use of apps, websites, or other forms of technology. Based on these lectures and readings, you will write reports every few weeks ( i forgot how many, maybe 3 reports) and in between those reports you will develop 2 papers in which you design a prototype for a chosen health equity issue you wish to address. Throughout the semester, you will also work in a group on a specific project of your groups choosing. This can involve code but it can also be completely free from it. It depends on how your group wants to tackle it. This project has milestones which will need to be completed in addition to the research and design papers mentioned above which all make for a pretty writing intensive course. For our project we made a high-fidelity non-functional application using FIGMA so if designing is your thing, you'll enjoy this course. This class feels like a combination of AIES, Ubiquitous computing (only the good parts), and HCI. Overall, I enjoyed this course and would recommend it. Rating: 4 / 5Difficulty: 2 / 5Workload: 10 hours / week - vsibVbdFfYHQ84sN6cGhvw== January 2, 2026 fall 2025 [Introduction to Health Informatics](https://www.omscentral.com/courses/introduction-to-health-informatics/reviews) I actually really enjoyed the lectures for this course which were a highlight for me. Dr. Duke was able to bring together aspects of healthcare with technology rather seamlessly. I have a biology background, so this portion of the course was a welcome surprise. As others have said, this course can be divided into 2 halves. Lectures, quizzes, and labs in the first half and a group project in the second half. I enjoyed the lectures so I had no issues with the quizzes. The labs were pretty straightforward and for some of the labs you were completely guided through them by the TA's. Keep in mind though, that for some labs most of the time will be needed in setting up the proper environments which can be a pretty big headache for some people. But overall, I cant say I learned too much from them. The group project, as always has a lot to be desired. I was proactive and tried getting a group early on but was still left with teammates who did jack. Throughout the program, group projects have been my biggest gripe and one of my main sources of frustration. I don't understand how some of these people have jobs at FAANG or other giants and end up contributing so little. Anyways, I was able to get a high A but to say I learned a lot would be an overstatement. I enjoyed the healthcare aspect of this course way more than the technology aspect so there's some bias on my end. For the first half, I was on Ed discussion constantly but for the second half, I maybe went on once or twice a week. The TA's were great, some of the best in the program. They were quick to answer any questions and provide good guidance if needed. So the class was better than I thought it was going to be based on previous reviews but still not the best. Lectures: 5/5 Labs: 2/5 TAs:5/5 Project: 1/5 Rating: 3 / 5Difficulty: 2 / 5Workload: 10 hours / week - sjjStLXYWzrnvOb/j7kxvQ== January 2, 2026 fall 2025 [Data Analytics and Security](https://www.omscentral.com/courses/data-analytics-and-security/reviews) Join this course if you - want an easy B or C grade - Light coursework - Just care about passing, not really understanding anything Do not join this course if you - want a satisfying A - want to actually learn anything about cybersecurity - Have a low tolerance for bad TAs Having said that - here's my experience with this course 1. THIS IS NOT A CYBERSECURITY COURSE - This is a 100% STATISTICS course. Barring maybe a throwaway module on security concepts, the entire course is about statistics. Linear models, regression models, clustering etc and then implementing those in R. Final project is also pure statistics, finding some patterns and trends in data - zero cybersecurity. As someone with no interest or background in statistics this course was entirely awful - and I ended up just focusing on whatever needs to be done for grades. I didn't learn anything relevant or useful that could apply to any real world cybersecurity scenario. As a policy s 2. TA's will ruin this course for you - The assignments are vaguely worded, the rubrics are just as vague and the TA's make random judgement calls with no real recourse. Blanket "no regrades" are issued by TAs and the professor is hands-off, blaming students' grades on "low effort" (his words, in an actual Ed post). No reflection whatsoever that an entire class of 100+ students got bad grades and were complaining daily about TA's. Instead he blamed it on low effort. Students lost 5 to 10 points because TAs thought the paper had too many bullet points, or they didn't agree on where periods should be used, or they don't agree with the grammar structure or format of the write-ups etc. 3. Group project is a luck of the draw - you're paired against randoms for the group project. I had an awful experience with one person who literally did nothing (not even one word contributed to the final reports). The other one refused to hear any input and made the "group" project his personal project. Rating: 1 / 5Difficulty: 1 / 5Workload: 6 hours / week - 2Me+AQwmW5DaTYXjYAnU8g== January 2, 2026 fall 2025 [Time Series Analysis](https://www.omscentral.com/courses/time-series-analysis/reviews) It is a good class. The instructions are very detailed and the topics are interesting. If there are any improvements, it would be the question for projects can be a lot more clearer. Sometimes I had to input a lot more codes simply because what it asks for. Rating: 5 / 5Difficulty: 5 / 5Workload: 15 hours / week - MeZgjPPmk12++gjERVeq9g== January 2, 2026 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) This was my first course in OMSCS (Fall '25). I finished with a 96/100. I initially came into this course assuming there would be a lot of writing involved, and I was correct. You will write A LOT and as someone who doesn't really like writing papers, the classwork was not very enjoyable for me. With that being said, as long as you follow the instructions on the HW's and projects and base everything off of the course material you will get an A on them, they're just time consuming. The four quizzes are the hardest part of the course, but will also force you to learn the most. Each quiz consists of 5 essay questions - each with several different sub-components. They're fully proctored, no notes or outside help - just your memory. You're given two hours to complete them which is tough due to breadth of each question and the depth of your responses. It was also really difficult to digest any of the required reading material that you're quizzed on. Grading can also be somewhat inconsistent from what I experienced. The course is front-loaded like other people have mentioned. In Week \#9 we had an exam due, a quiz due, and a project check-In due. Once you've made it to this point - the rest is smooth sailing. Exams were proctored but open-everything. They are easy if you’re okay with a B on them - which I was. The projects (Individual & Group) are structured the same. If you follow all of the instructions and choose a good task/interface to improve you’ll be fine. The group project comes with all of the same drawbacks of any other group project. I was able to fulfill all of my class participation points by doing all of the peer reviews and taking some surveys for other classmate's projects. In short, the class is not inherently difficult it’s just time-consuming and requires a lot of writing. I found the material very interesting and the lectures very easy to digest. Dr. Joyner is so good at using examples to explain different concepts. Rating: 4 / 5Difficulty: 3 / 5Workload: 18 hours / week - CNFJRTK8LziCE4STdYeT/Q== January 1, 2026 fall 2025 [Machine Learning](https://www.omscentral.com/courses/machine-learning/reviews) This was my last course of OMSCS and the one that I was most worried about from reading the reviews on here. The course has seen major changes that have genuinely made it easier to pass the class. However, I still feel that this course doesn't do an adequate job of giving you concrete knowledge of ML. Pros: 1. Regrade Requests: The course has introduced the ability to correct issues found by graders for half points. So if you receive a 70% on a report and adequately address all issues highlighted by reviewers, then you could receive a maximum of 85%. I personally did not use this mechanic but others seemed to benefit greatly from it. 2. Quizzes: The quizzes allow for 1 sheet of notes and a calculator. You are also given multiple attempts. The multiple attempts alone made it extremely useful for me as I typically used 1 attempt to get a baseline of my current knowledge and gaps that needed to be filled. 3. Exam: The course has done away with the mid-term exam due to the workload of the reports to where we only had a final exam. The final exam is different from the quizzes and I'd argue is easier as it focuses more on concepts centered around the algorithms covered in the class. Cons: 1. Hidden and known rubric issues: In recent years, the requirements have become more clearly defined. You are told exactly what libraries you need to use, what plots are required, and given SOME details on how to structure the papers. However, the known requirements were honestly difficult to cover. For example, In A1 they required an absurd amount of plots and specified that they must be visible without zooming in. This forced me to drastically weaken my analysis just to include all plots. The known rubrics also went through MANY iterations and changes as the assignment deadline approached which I found frustrating. In A1 for example, the TAs defined a requirement, removed it, and defined it again in the span of a week. The hidden rubric also still exists and graders are using requirements that are not clearly defined when grading your assignment. 2. Grading delays: The grading was incredibly delayed and students had no idea whether they should continue or drop the class as grades for A1 did not come out until days before A2 was due (between these two assignments, that's 25% of your grade in limbo while the drop deadline was closing). The course also tells you that every report is iterative from the previous report in terms of the feedback that you receive. So you're expected to address feedback from A1 in A2 and the other reports. This didn't have a major impact for me and I only had to re-write small portions of my A2 report but this definitely affected other students. Additionally, I found it frustrating that regrade requests for A4 (the final assignment) were not available, with the stated reason being that grading delays pushed the timeline to essentially the end of the semester. Recommendations: 1. Reports: I personally got 92%, 99%, 100%, and 93% across all reports. You are given the option of doing extra credit for an additional 10% but with the already defined requirements, I found it difficult to manage the page limit as it is and opted out of doing the EC. My recommendation would be to clearly define the hidden rubric requirements as early as possible so that you do well on A1 and are not compromised on A2 with the grading delays. Ed Discussion and Office Hours were my main source of assessing the requirements. The TA's will not give clear answers and will give suggestions. I would treat those suggestions as requirements for your report. Also, the known rubrics will change over time so keep an eye on Ed Discussion for the latest version of these documents. I also think there is a disconnect on the purpose of these reports that is not adequately covered in the known and hidden requirements that trips up some students. The primary goal of these reports is to analyze the algorithms and their behavior on the provided datasets. The objective is not to maximize performance metrics or aggressively tune hyperparameters, but rather to explain why the algorithms behave as they do, interpret patterns and trends in the results, and connect those observations back to the underlying theory. Finally, I believe that completeness is valued more than accuracy which is unfortunate. I found myself constantly cutting or reducing my analysis to meet all of the requirements which made my analysis very light and surface-level. A4 was EXCELLENT in my opinion as it was light on plots and heavy on analysis. Overall, This course is clearly improving and It's clear that they're taking the feedback from previous semesters into consideration. However, I still think there is room for improvement. Rating: 4 / 5Difficulty: 4 / 5Workload: 12 hours / week - Hlbv1xErB9n1pHPQKEPY4Q== December 31, 2025 fall 2025 [Special Topics: High-Dimensional Data Analytics](https://www.omscentral.com/courses/special-topics-high-dimensional-data-analytics/reviews) ISYE 6525 - HDDA - is the first class I've taken at OMSCS that actually feels like what I expected when I enrolled into a master's level program. Lectures are short with no nonesense, and TAs will absolutely not hold your hand to guide you through the assignments. Coming into this class without knowing how to do matrix calculus and without being comfortable in numpy was tough. The first HW asked me to solve a linear regression without the professor explaining what a linear regression was. I was able to come arround and grasp the necessary material, but it's always frustrating when you realize you're paying money to self-learn. And even still, most of the assigned readings went straight over my head. There is no single textbook, but snippets of various (non-required) books and papers to read for each module. You'll have one module every 2 weeks for about 1 hour of lectures, 60 pages of text, and 1 HW. HW can be completed in Matlab, R, or Python, or any other language you choose, though example codes generously provided by the professor only come in these 3 languages. The 2 exams are essentially slightly tougher open book HW problems with 1 week less to complete them. Grading is extremely generous, actually insultingly so - I was frequently given full marks despite my code producing the wrong output. I found the lectures and the professor's style of teaching disappointing, and it seems most other reviews did as well. 1 hour's worth of lectures per 2 weeks is not enough for more than surface-level knowledge. It always bothers me when I hear a professor say "here's this formula. It can be proven to be accurate but I'm not going to show you how." You'll get a ton of that in this course. Don't expect to see proofs or derivations in the lectures themselves. This problem is compounded by the expectation that you will be using libraries to get your code to work (rather than implementing the algorithms yourself), so it'll be tough to grasp the details of what you're doing. Frustratingly, I sometimes found myself copy pasting the example codes without understanding how they work. Yet this was enough for an A. In summary: although the material was very interesting, I can't confidently say that I've learned it. Rating: 2 / 5Difficulty: 3 / 5Workload: 7 hours / week - Hlbv1xErB9n1pHPQKEPY4Q== December 31, 2025 fall 2025 [Applied Cryptography](https://www.omscentral.com/courses/applied-cryptography/reviews) CS 6260 - AC - is the most enjoyable class I've taken in the OMSCS program so far. Essentially what you'll be doing is taking the role of a hacker and try to break various presented encryption schemes. For the 2 exams and the 5 written assignments you'll be presenting theoretical hacks on paper, and for the 2 coding assignments you'll be designing and implementing hacks in Python. In other words, you will mostly be solving puzzles. So, you need to be comfortable with relying on your intuition and the provided examples - if you're experienced in playing Zachtronics or similar computer games you should be fine. The textbook is not required reading, but the professor is extremely clear and rigorous in her explanations, to the point where sometimes I would zone out of the lectures. Grading is overly strict - if you do not use exact language expected or do not fully show your work you will get points deduced, though you can dispute with the TAs. The cutoff for an A is at 80% score to make up for it. The assignments were very helpful in understanding the lecture content. I'm not giving 5 stars because the second half of the class (dealing with asymmetric encryption) had a noticeable drop in quality due to getting bogged down in the details of number theory. There was not enough time to cover the topic in depth, in sharp contrast to the first half of the class. Additionally, I wish we spent more time on practical applications and got to see real life examples. Finally, on the same note, the class did not seem to be rigorous enough for a master's level course. For instance, there were no (mandatory) readings assigned and we never had to prove that a scheme was secure (only insecure). Those of you who are privay concious be warned - you will have to install Honorlock spyware to take the 12 quizzes and 2 exams! Recommend using a live USB. Rating: 4 / 5Difficulty: 2 / 5Workload: 6 hours / week - zhE+Nal3x1LLOxyCcniiUg== December 31, 2025 summer 2025 [Database System Implementation](https://www.omscentral.com/courses/database-system-implementation/reviews) - This course felt like a beta course. It is not a graduate level course (I doubt if this can even be at undergrad level)! The content could have included other topics like Logging, Recovery, Transaction Management, Distributed and Cloud databases, Examples for the features described from modern databases but apparently another course is being prepared for these. If you are looking for a solid understanding of relational databases, just read the recommended book "Database System Concepts, 7th edition (https://www.db-book.com/) and may be go through Andy Pavlo’s youtube videos instead of taking this course. - As others said, too much time is given for C++ concepts in the lectures, thus depriving of chances to cover other database concepts. C++ must be made a pre-requisite instead. There is a programming assignment just to check C++ concepts, that could have been used for solidifying other database concepts instead. - TAs were mostly low key on Ed during the summer semester. They took many days to respond to student enquiries. I took a couple of courses before this, and TAs in this course are the least participating ones. Ed forum did not see much activity as the TAs and Professor didn’t respond to student queries within a few days in general (I would expect TAs to field most of the questions within a day or two). There was a time when all of them went completely silent for 4-5 days\! - Lecture slides contained many mistakes from the first run of the course and were not corrected in this run too. It seems like not enough attention or effort is spent to improve the online version of this course. If you are coming to this course expecting GIOS type of rigor and discipline, you’ll be disappointed\! - Exams and exercise sheets were not that challenging. Programming assignments don’t have much guidance via comments. However if you spend like 4-5 hrs per week, you can end up getting an A easily (assuming you have C++ knowledge). - This course’s curve is the most lenient (if you scored \>= 80% you get an A grade, otherwise a B) of all the courses. 90% of the students got A! If I knew this beforehand, I’d have studied even less for the exams and exercises and I would have spent more time in reading the book. Rating: 2 / 5Difficulty: 1 / 5Workload: 5 hours / week - 6v6NWG6Kl/hPv2eJJuS8gA== December 31, 2025 fall 2025 [Introduction to Graduate Algorithms](https://www.omscentral.com/courses/introduction-to-graduate-algorithms/reviews) I took GA as my last class, but having done that, I would recommend trying to take it a couple of semesters before you intend to graduate as I'm sure that would make it feel way less stressful. The levels of anxiety that GA can generate are really pretty nuts, so please take this advice seriously. It sounds strange, but other than the stress, I don’t really have a ton of complaints about GA. Brito and the TAs seem like genuinely nice and caring people, and I can’t really fault them for any of the negative aspects of GA. They seem to have experimented a lot over the years with how the class is run. They have incorporated student feedback, while still keeping the class rigorous and substantial. I believe they are doing their best. The exams felt mostly fair, and the grading was even generous at times. The only real issue I had was that it wasn’t always obvious what kinds of mistakes would result in massive point deductions and which would be treated more leniently, so I recommend getting as much clarification as possible about that from the TAs. Generally though, if I finished a test feeling pretty good about how it went, that was reflected in the grades, and if I felt like something went wrong, the grades reflected that too. I recommend attempting every single homework and practice problem that is assigned or mentioned in a post by the TAs, including the coding problems, and the extra practice problems. Doing that along with watching Vigoda's lectures and reading DPV should be sufficient to prepare for the exams. Before GA, I had previously taken ML4T, RAIT, ML, DL, CN, GIOS, HPC, HPCA, and Netsci, and I earned A’s in all of those classes. GA was my first B, and I missed an A by less than half of 1%. But I’m grateful that I got through it in one try and graduated OMSCS without having to repeat it. Rating: 4 / 5Difficulty: 5 / 5Workload: 24 hours / week - AsXSpPZZ36Buac6bbnSyRA== December 30, 2025 fall 2025 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) First class in the program, mech engineering bachelors from 10 years ago, some coding experience from the past few years of self-teaching. Overall, I learned a ton about how computers and operating systems work! I thought it was super interesting how applications interact with the OS, all the parts that make up an OS, and there was so much I learned about what goes on behind the scenes it made me in awe of computing systems. It felt like more than 17 hours a week. I would recommend starting projects ASAP and try to stay ahead of the schedule provided for the lecture modules. It helps watching the corresponding modules for each project before starting, so you should complete them before the project is even released ideally to avoid concentrating lots of those hours in heavy weeks. Projects - 100, 100, 110 Midterm - 77 Final - 93 Final grade - A Hours / week - 17 Projects Directly related to some of the chapters conceptually but you’re pretty much on your own to learn the coding. The time below includes the ReadMe write-up which I spent 8-12 hours on for each project. Project 1 - 70 hours. It took a ton of time for me since the only experience I had in C was from cs50 Harvard a long time ago. The warm up parts did a nice job of easing you into the main parts of the project though. It involved using sockets to send and receive data, then implementing parts of a provided library, then making the library multithreaded. Project 3 - 40 hours. It was the easiest by a lot in my opinion. Inter-process communication between cache server and proxy to serve requests to clients. Project 4 - 60 hours. This was the most rewarding but perhaps the most frustrating. You need to implement a distributed file system using gRPC. It took a really long time to understand all of the steps clearly but it was cool seeing it working and keeping all the files across all clients and the server in sync. I probably spend an extra 10 hours doing the extra credit. Tests The midterm was shorter and didnt include as much info as the final. I thought that both were pretty fair; there was a balance of facts and memorization with some questions where you had to apply your knowledge. I probably put in 15 hours for the midterm, and 30 for the final as I went through all my notes thoroughly, did a ton of practice calculations, made and practiced flashcards, etc. Lecture Modules (17 total) The lectures are really good and I only had to seek supplemental knowledge / clarification a few times over the course of hundreds of 1-5 minute lecture videos. I took thorough notes and spent and average of 3-5 hours on each module. Good The amount of knowledge you will take away from this course. I didnt know a lot about computers in general before this course, so I went off on some learning tangents in the middle of the videos. Overall I feel like I have a much better base than before. Slack was awesome to work through problems with other students and get help, but I did not like Piazza as I hate their UI and found it very hard to use and find what I needed. TAs were really helpful and their attitude in answering questions was proportional to the intelligence of the question. Despite all the hidden stuff lots of people including me complains about (see below), I thought the projects were really well put together and were super captivating. Bad In project 1 a little, and project 4, it did feel like we were herded to implement the solution in a specific way. It did take a lot of extra time to figure out the abstracted functions / files in project 1, and in project 4 it felt limiting only being able to edit and submit certain files. However, after spending some time with the code it becomes clear why it is structured this way and in the end I dont have any major qualms with it. The exams are weighted too heavily in my opinion. A project takes ~50 hours and is worth 15%, where exams are 25%. Some exam questions test your memory on little details, so if you lose 5 or 10 points on one of them, it is almost equivalent to 5 hours of project time. I get that the concepts are important and we should know them thoroughly but I would be more happy with the exams and projects being equal, especially since the projects are so grueling and time-intensive. There probably wouldnt need to be such a large curve this way. There are a bunch of errors in the quizzes and some lecture videos, I would have expected them to re-make the videos at some point in the past 10 years instead of leaving errata notes below which are very easy to miss. Rating: 5 / 5Difficulty: 3 / 5Workload: 17 hours / week - ymZc+tY36sXteFxpQeZ28Q== December 30, 2025 fall 2025 [Distributed Computing](https://www.omscentral.com/courses/distributed-computing/reviews) I took this course in Fall 2025, and it covered topics I’m genuinely passionate about in distributed systems. I finished the course with an A (88%). Overview The course starts relatively slowly with lectures, followed by Project 0 (intro), Project 1 (client–server), and Project 2 (primary–backup replication). The lecture material is good, and both the required and optional research papers are excellent (long term). Many are still highly relevant in industry today (saved and reading them now after the course :) ). Working knowledge of Java is needed to do well IMO as a good amount of coding/debugging is needed. The real challenge begins with Project 3 (Paxos) and Project 4 (KV Store). IMO, Paxos is the harder of the two. I worked on the projects almost every day, and while demanding, the experience was rewarding. Running tests locally (macos) helps with time and quicker iteration. That said, there are some notable downsides: The DSLabs framework has a steep learning curve. Even by the end of the course, I didn’t feel I fully understood all of its internal workings. Some tests are extremely strict, especially with tight timeouts and DSLabs-specific requirements (e.g., running with --checks for idempotency, checking correct equals() / hashCode() behavior for search tests, etc.). It’s worth noting that passing all tests is not required, and the grading curve helps significantly. Pros A wealth of high-quality material, especially valuable if you already have experience building software components from the ground up. Project4 reference implementation helps and didn't find it confusing. Well-structured lectures with a great selection of research papers. Exams are easier than AOS, fully objective and with sufficient time. The trade-off: each question carries more weight, so mistakes are costlier. Cons The test framework for Projects 3 and 4 is rigorous. Must start early and invest time understanding readme.md and DSLabs framework. Final Thoughts Overall, this is a strong and rewarding course for students interested in distributed systems, especially those who enjoy both theory and hands-on implementation. If you’re willing to commit time consistently and don’t get discouraged by test failures, you’ll learn a lot. That said, I think the course could benefit from leaning more clearly toward either learning (theory) or implementation, rather than straddling both as heavily as it currently does. Rating: 4 / 5Difficulty: 4 / 5Workload: 35 hours / week - uGdPLFYuNjNE0R+60hFMKg== December 30, 2025 fall 2025 [Statistical Modeling and Regression Analysis](https://www.omscentral.com/courses/statistical-modeling-and-regression-analysis/reviews) This class is overbloated garbage. Everything feels like a chore. They shoved 2 midterms, both coding and mc into it and the instructions for the coding portion is a multistep mess. There's a crappy group project but you cannot even pick a topic you want to do. The least offensive portion of the course is the homework, but even that is overly long. Some of the TAs are also very condescending and feel the need to add extra bs to their responses to student's questions. Just take another elective over this trash class. Rating: 1 / 5Difficulty: 3 / 5Workload: 10 hours / week - toohORXUybDr8ej6qtCbDA== December 30, 2025 fall 2025 [Introduction to Information Security](https://www.omscentral.com/courses/introduction-to-information-security/reviews) This course felt more like a bunch of mini-courses, with most modules having a different set of TAs. It's entirely CTF based now. Most projects had flags that you'd submit, and the tasks that required code submissions ran it through an autograder. There's no subjective grading: you know your grade after each submission. There were some assignments with submission limits, but they were lenient and I never felt much pressure. This course will tear you up if you don't have a decent coding background. I took two years of Python in undergrad and still had to take some time brushing up on things. Some modules were better than others. MITM was easy and made for a good warmup. Malware analysis consisted almost entirely of reading reports and was kind of a letdown. Binary exploitation was tough for a lot of us (including me) but it was very informative. Extra credit was available on some assignments. You can't depend on it being there, but they do offer it at least sometimes. I'd say about 3 extra points in total were available on your final grade if you went for all of it. The professor was entirely absent. Not an announcement post, not a lecture video, nothing. The class was entirely run by TAs, at least from my perspective. That said, the TAs were helpful and the discussion boards will be your friend. You'll need to know how to do outside research (follow the syllabus) if something isn't familiar to you. The workload varies a lot. MITM took me ~10 hours or less, whereas binary exploitation probably took me at least 40. VM setup worked just fine on my Windows laptop. You'll want to know basic Linux commands (how to navigate the filesystem and run scripts, for example). I'd suggest doing some practice on HTB Academy (\$8 a month with your student email) and/or picoCTF (free). There's other resources out there as well, like DVWA if you want to practice Database Security before you start the course. Overall, it was difficult but not unbearable. I got an A while working full time. I passed the OSCP in 2024 which helped a bit but there was still a lot of learning I had to do. Rating: 3 / 5Difficulty: 3 / 5Workload: 25 hours / week - tQDYQZAdQEOyu+fkV4eVtw== December 29, 2025 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) TLDR: While I finished the course with a high A, I had mixed feelings about this class. In particular, I felt like there was a significant imbalance between the course's workload (somewhat high) and the actual depth and difficulty of the work (pretty low), which I feel led to me disengaging somewhat with the material; I found myself wishing topics were explored in much more depth. I did not feel like the team project actually was able to dive deep enough into the design process to justify its existence. This course is pretty evenly divided into thirds. For the first 1/3rd of the course (the "Content" phase), you are watching the entirety of the class's lecture content, along with completing a weekly homework assignment (Homeworks are 4x5% = 20% final grade). The course content is divided into two major units, Principles (essentially the theories behind interface design) and Methods (the design lifecycle, how to prototype and evaluate an interface). The lectures are excellent, Dr. Joyner is an exceptional presenter and brings very good energy to the videos, they are very easy watches and convey the necessary information very well. I found the actual content behind the "Principles" unit to be much more interesting than the "Methods" unit, which often felt a bit surface-level (I'm a grad student, I know what different types of data are and how to use statistical tests), but the course endeavors to be entry-level, so whatever. The homeworks each consisted of answering 4 questions in 8 or fewer pages. Like many things in this course, it felt like these were graded quite easily and straightforwardly. The second third of the course (the "Practice" phase) felt like it ramped up the workload quite a bit. This phase consisted of reading the associated texts with the course, completing four quizes (4x5% = 20% final grade), along with working on the individual project (15% final grade), and taking 1 out of the 2 course tests (10% final grade). The readings varied in quality considerably. Many of them felt like "slightly-reworded-lecture-content-but-worse", but a few of them were interesting. The quizzes felt very fair. Studying the lecture content felt straightforward (like I said, the lectures were good). One question on each quiz was from the assigned reading, and the instructor informed us ahead of time which reading would be on the quiz (I dunno about this one, this feels maybe a little *too* nice). The project consisted of selecting a design task, performing needfinding for that task (for 95% of people, this meant posting a survey for the class), designing three prototypes, evaluating these prototypes (for 95% of people, this meant posting a survey for the class), making a higher-fidelity final prototype, and having people evaluate it (for 95% of people, this meant posting a survey for the class). I didn't really mind the project, although it appeared to be a massive procrastination trap for a lot of people. It did sometimes feel like a lot of the survey responses were low-effort (we got participation points for completing surveys). Writing the project report (max 25 pages) felt like the same straightforward grading as the homeworks; if you do everything the assignment asks, you can expect a 100, no surprises. The final third of the course (the "Application" phase), consisted of a team project (15% final grade), along with taking the remaining test (10% final grade). If that sounds a lot easier than the last phase... yep. The tests were open-note, open-internet. They felt like the kinda assignment where its extremely easy to get an 85%, easy to get a 90%, and quite difficult to get a 100% on (which, coincidentally, is the opposite of the rest of the course). I don't have much more to say about them. The team project was nearly an exact reboot of the individual project; the major differences were an increased page limit on the report (max 40 pages), and the vague direction that our prototypes should be higher fidelity. I didn't like this. It didn't really feel like we had a chance to dive deeper into the design process, since (as mentioned), I felt like poor survey responses were kinda bottlenecking the interface design anyway (the instructor plans to require interviews for the team project feedback in the future, which I do think is a good idea). In addition, there is also the classic team-project roulette; my team had one person completely unresponsive, and another who had to be prodded quite a bit to do work. I think these kinds of projects are fundamentally unfair, end of story. The remaining 10% of the grade comes from course participation, for most people, this meant spamming low-quality survey responses. I wish there was a better way to align incentives to encourage thoughtful responses, but I can't really think of anything. Dr. Joyner intended this course to take ~10 hours per week. I think it mostly does, with the caveat that unless you're willing to work a bit ahead, you will definitely have weeks that exceed that, and that the final third of the course is much easier than the other two. I'd probably scooch a quiz or two into this final phase if I were running the show, but it's not a huge deal. I would advise anyone taking this course to heed the instructor's advice about proactively forming your own team instead of doing the matchmaking survey (to increase your odds of avoiding slackers), and to be proactive with the project work. But the class is very straightforward (potentially to a fault) if you don't mind things being somewhat introductory, and having a moderately bumpy workload. Rating: 3 / 5Difficulty: 3 / 5Workload: 10 hours / week - Leq5tv8IK8tghRyJLzn6eA== December 27, 2025 fall 2025 [Special Topics: Applied Natural Language Processing](https://www.omscentral.com/courses/special-topics-applied-natural-language-processing/reviews) This was by far the worst course I took on the programme. Don't expect to learn much from the classes (as they have nothing but a teacher reading the slides without taking note of anything) - most of the things I learned came from putting the class transcripts into ChatGPT to get explanations. The assignments are disappointing as well… they were useful in a certain way because I had to learn how to work locally using .py files (in a "object-oriented way"), but I found them pretty easy (as much of the code is provided). Overall, I learnt some stuff (and the course content is pretty up to date), but it wasn't worth my time or money. Rating: 2 / 5Difficulty: 2 / 5Workload: 7 hours / week - BbZ3VI+UXIBBvTaYgCBzpw== December 24, 2025 summer 2025 [Introduction to Cyber-Physical Systems Security](https://www.omscentral.com/courses/introduction-to-cyber-physical-systems-security/reviews) This is for Fall 2025. I really enjoyed CS-6263 and found the projects fun…but that could be due to my background in logic and circuit design. I echo the same advice others have given — start the projects early. Project 1 took about 25 hours total and consisted of a part A and B. Part A only took about 5 hours, including reading up on how to use the tool and watching tutorials. Part B was more challenging but in a fun way — I actually completed it in 15 hours but spent another 5 hours fine-tuning things. Project 2 took about 15 hours. Ladder Logic is a breeze if you’re familiar with logic gates and parallel signal propagation. If not, then it could take 2-3x longer to finish the project while you brush up on related concepts. Project 3 was different from past semesters and only took about 5 hours to practice sniffing for ICS devices. Project 4 gave brief exposure to machine learning. It seemed daunting at first but turned out easier than I expected. It helps if you’re familiar with Python or object-oriented programming. You are provided with a working skeleton model and have to fill in additional portions of code to make the project functional. Once you get your ML model to run properly, then you further refine and optimize your machine learning algorithm to hit the grading targets for accuracy and relevancy. I was a little worried at the beginning of the semester after reading some of the other reviews because the difficulty level can be deceiving. Fortunately, my background in computer engineering served as a great foundation for all four projects and I finished each project with anywhere from 5-9 days to spare (primarily because I started projects early). I actually struggled more with the exams. It is true, the lectures are completely independent of the projects. I didn’t mind this as I could focus more on the projects early on and come back to the lecture material later when it came closer to the midterm/final. You are allowed one page single-sided notes for the midterm and one page double-sided for the final. The lectures are all done well, some of the best production values I’ve seen in OMSCS so far, and I found the material all very interesting. Still, I was thrown off by the wording of some exam questions and received a C on the midterm and a B on the final. I still finished with an A overall in the course by averaging 98% across all projects. There is also a 20-minute video presentation you have to do based on a research article. It is an easy 100 points. You get to select your presentation date and I quickly picked the latest available week for due dates. I suggest you do the same so the presentation doesn’t interfere with your first or second project. By the time you’re on project 3 and 4, the pace of the course really slows down and you’re in a lull in the semester so it’s a perfect period to then focus on your presentation. I recommend this class for any of the OMS specializations, either as a requirement or elective, because the course is interesting, the projects are neat and fun, and the difficulty level/time commitment is very manageable for balancing family and career. One last remark, I have to give credit to the amazing TA support team. The TAs ran Ed Discussion superbly and were responsive and gave helpful advice. Office hours were also extremely helpful. I was kind of shocked at how few people attend office hours; sometimes it was just me and the TA one-on-one (which was great for getting personalized help). Maybe everybody else knew what they were doing and didn’t need the help but I was grateful for how accessible the TAs were. Whenever I was in a quandary, or found the project instructions unclear, it was quick and easy to get clarity in office hours or through the discussion board. Rating: 5 / 5Difficulty: 3 / 5Workload: 10 hours / week - cvUKRHrSDa+Z2dn5TUe48Q== December 24, 2025 fall 2025 [Database System Implementation](https://www.omscentral.com/courses/database-system-implementation/reviews) Medium-effort, high ROI course. 4 Assignments 3 quizzes 2 exams Great class if you are interested in understanding how databases are built from scratch. The assignments focus on implementing a beta version of BuzzDB in C++ and iteratively improving it over the course of the assignments. One of the nicer things is that there are no hidden test-cases. Passing the test-cases locally almost always guarantees a 100% on gradescope. B+ tree (assignment 3) was the most challenging one. Quizzes: These are proctored quizzes (via honorlock) that mainly focus on the lectures. Combined make up around 25% of the grade. They aren't too bad , but there are 3-5 questions that can seem from material not included in the lectures but need general database knowledge to answer Exams: Same as the quizzes but with the material from the papers, especially the final was mostly from material in the papers. But the professor mentions the important sections from the papers relevant to the exam. My advice would be to focus on those. Curve 85% was an A , it looks like the course is getting tougher with time. % of As has decreased compared to previous semesters. One of my criticisms is the weightage of assignments relative to quizzes, quizzes seem like beta exams, and sometimes I felt that they weren't really needed . Instead they could add up-to 2 extra assignments dealing with in-depth concepts from databases. This is where the course missed the bar slightly. Overall , a great course, put in the effort and you will be fine. The professor and TAs genuinely care and want the students to succeed. My grade A - (89%) Rating: 5 / 5Difficulty: 3 / 5Workload: 14 hours / week - 2c1btKEcjhtxtHHB8f2rMg== December 24, 2025 fall 2025 [Knowledge-Based AI](https://www.omscentral.com/courses/knowledge-based-ai/reviews) Background: 1st semester student, Undergrad CS major, working as a Data Scientist for less than a year. Finished the course a month early and ended up with an A(91.89%). Pros: - The lectures are very interesting and enjoyable, and they are presented in a way that’s easy to understand. - The coding assignments aren’t too difficult and are manageable. - The TA and Dr. Joyner are great and respond quickly when help is needed. - The integration with gradescope is cool, you are able to submit coding assignments up to 40 times and it auto grades so you can see your grade right away. Cons: - The lectures don’t align very closely with the assignments; the assignments aren’t really AI focused and feel more like general coding tasks. - The writing assignments feel somewhat useless and repetitive more like busywork that could be avoided. - I received feedback on early assignments, but later in the course I didn’t get any feedback at all. Homework(15% )- 90/100: These are writing assignments (journals) based primarily on lecture material. Make sure to follow the prompt questions closely and answer them clearly and completely. Demonstrate a strong understanding of the relevant lecture concepts and apply them accurately. When a prompt asks for a diagram, ensure that it matches the one shown in the lecture exactly. In a previous assignment, I mixed up two concepts and received no credit for either, which resulted in a C on that assignment so accuracy is very important. Exams: Midterm(7.5%) - 70.91/100, Final(7.5%) - 92.72/100: I’m not a great test taker, so I didn’t do very well on the exams. They aren’t too hard since they are open notes and open internet including AI, but you still need to understand the concepts really well. On the first exam I struggled with time management and ended up turning to ChatGPT as a last resort, which didn’t help much. After that poor result, I made really good notes and used NotebookLM by Google to ask questions based on them for the second exam, and I ended up doing much better. I recommend that if you are unsure if a statement is correct to leave it unselected. Mini Projects: Performance(15%) - 98.5/100, Journals(15%) - 95.4/100: The coding assignments are fairly easy and similar to medium-level LeetCode problems, so they shouldn’t take too long, except for Mini-Project 2 (Block World), which was difficult and cost me a few points. Overall, the assignments are manageable. The writing assignments are short (max 4 pages), but I lost points for not including metrics related to efficiency and performance. ARC-AGI project: Performance(7.5%) - 100/100, Journals(7.5%) - 100/100: For the assignments, you’ll be solving ARC-AGI problems by creating an agent. I didn’t implement any real AI methods myself, what I did was design a specific solution approach for each problem. To achieve full credit on each milestone, you need to pass at least 6 out of 16 general test cases and 6 out of 16 hidden test cases. The journals can be repetitive, so feel free to reuse the same structure each time. Just make sure you include specific metrics for each milestone, including: Efficiency: Big-O complexity and actual runtime, Performance: Number of test cases passed Keep in mind that even though you only need 6/16 for both general and hidden tests at each milestone, you’ll eventually need to solve all of them for the final project. Because of that, I recommend completing as many problems as possible throughout the milestones rather than waiting until the end. Final ARC-AGI project: Performance(7.5%) - 84.38/100, Journals(7.5%) - 76/100: Each milestone (Milestones B through D) includes 16 general tests and 16 hidden tests, for a total of 48 general tests and 48 hidden tests across all milestones. I wasn’t able to solve 15 of the hidden tests, which left me with a performance score of 81/96. My performance wasn’t as strong as it could’ve been because I decided it wasn’t worthwhile to spend hours trying to figure out each hidden test for just a 1 point increase. The final journal grading is much stricter than the other journals. I answered every question on the assignment, but some parts were considered vague by the TAs, which lowered my score. I put in the same level of effort as I did for every milestone, where I earned 100 out of 100, but the TAs expected more for the final journal. I recommend being very clear and keeping in mind that the grading is stricter. Participation(10%) - 100 / 100: These points are basically free, and there are plenty of opportunities to earn them. I mainly completed peer reviews each week to stay ahead. After about two months, I had already earned the full 90/90 points and didn’t have to think about it for the rest of the semester. Rating: 4 / 5Difficulty: 3 / 5Workload: 12 hours / week - UxM4W8UQJZ4uBeXkBIQvBQ== December 23, 2025 fall 2025 [Introduction to Graduate Algorithms](https://www.omscentral.com/courses/introduction-to-graduate-algorithms/reviews) This was my least favorite course so far although I do understand the importance. Many of the algorithms are not practical but help establish a mindset on how to simplify. Students will learn how to assess the time complexity of an algorithm, some common approaches to simplifying and solving problems and how to deal with problems that may not have clear solutions. This I liked. I also liked the lectures, although they were all recycled from a former instructor. The homework assignments are graded but have zero weight on the final grade. Exams have the heaviest weight. The multiple choice problems are tricky and the grading is subjective and probably dependent on who graded your work and how they were feeling when they did it. It was hard to review exam results. You are not given direct feedback on multiple choice questions and for the proofs the feedback is obscure. I didn’t really care to try to interpret it once I had a B. There is minimal coding in the course. Most of the coursework involves solving problems in words, similar to writing proofs. There is a textbook for the course, Algorithms by Dasgupta. This and the recorded lectures are assigned in a disjointed order throughout the course, which disrupts the flow. The textbook is also concise and often requires the reader to fill in some ideas themselves, which required me to do a lot of rereading In conclusion, I found that the course useful, I mostly disliked the work (quizzes, exams and homework), the grading was harsh and subjective and the textbook was difficult to follow. Rating: 3 / 5Difficulty: 4 / 5Workload: 8 hours / week - 4v+GPNibbZHV4cDoKVlvvg== December 23, 2025 fall 2025 [Video Game Design and Programming](https://www.omscentral.com/courses/video-game-design-and-programming/reviews) As others have said, watch the lectures at 1.5-2x speed. The content in them is good though, there's a lot of really interesting stuff. Unfortunately I do think a lot of references that he makes will be lost on folks who aren't into gaming. There's a LOT of "history of gaming" style stuff, which makes sense when studying game design, but is much easier to grasp if you are into gaming and so have some context as to who Valve or id Software are. The project is what you make of it, but is easily the biggest time sink in the course. Coordinating with teammates is hard in Unity (merge conflicts are basically unsolvable, so you have to work on different things), so a lot of cognitive overhead comes from just that aspect of the project. As for actually learning Unity, yeah, you could just do it yourself - but Dr. Wilson gives some assignments that help introduce you to the engine, which can be intimidating. And I really do believe there's some value in working on a game with other people in a team to see how they do things, even if there is a lot of overhead in the coordination. Also, being forced to go through the process of making a game from start to finish, with all of the steps in between (alpha, playtesting, etc) is really a good exercise in forcing you to do steps you might want to ignore if you're just playing around on your own. All in all, not a hard class, but you can really go wild with the project if you want, which could end up taking a lot of time. Take this class if you want a semi-structured excuse to play around with Unity for several weeks/months, and if you want some interesting discussion of game design philosophy. Rating: 5 / 5Difficulty: 3 / 5Workload: 20 hours / week - Flq5Ybni4B0gY/9Ddy8jjQ== December 23, 2025 fall 2025 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) This is my first OMSCS course and I feel I learned quite a bit. I did not formally study Computer Science in my undergrad so everything over here was pretty much new to me or things I didn't know in a lot of detail. I really enjoyed the projects and I feel that was where I learned the most. The mid term was relatively easy but that could also be because the first two modules are easier than the last two. The effort I put into the course was quite sporadic, to be honest. I mostly spent the weekend before project deadlines working on the project. This is not how I like to do things but I just joined a new team at work and there was a lot going on so unfortunately this was the case. I would recommend getting headstart on the projects because there were really times when I was so stressed and worried that I wouldn't be able to complete the project but I was lucky and did well on the projects. The end term was the hardest for me and I barely got 48 hours to prep for it but that was because of my personal circumstances. However, because I did well on mid term and the projects I still managed to get an A. Overall, I feel if you keep up with the schedule they recommend, you can comfortably do the course. You get plenty of time between projects as well. The exams are MCQ and fill in the blank style but similar to the quizzes in the lecture. The end term is relatively harder and I would recommend allocating good chunk of time for that. The professor and TAs were all very nice and gave pretty good feedback as well. Rating: 4 / 5Difficulty: 2 / 5Workload: 5 hours / week - lVaErvC+H+S2COrzPeOalw== December 23, 2025 fall 2025 [Introduction to Health Informatics](https://www.omscentral.com/courses/introduction-to-health-informatics/reviews) Finished the course with an A, achieving a 102.88 % Background: Bachelor's degree in Computer Science from a university ranked \#350-400 out of 436 National Universities in U.S. News English is my second language (TOEFL score: 95/120) 1 year of experience as a full-stack developer and 6 months of experience in data analytics Overall: This class is fairly easy, especially if you have experience with full-stack development or have built applications before. If you’re interested in working in the healthcare industry, this course provides an entry-level introduction to using REST APIs and interacting with a testing server. You can be as creative as you want with the project and even try out new tech stacks you’ve never used before. As long as you put in reasonable effort and build something enjoyable, getting a good grade is very achievable. Labs (39.07 / 35%): There are six labs plus two extra credit labs, and as long as you follow the instructions, you should get full credit. Some students on the forum complained that the setup instructions didn’t work in their environment. If you’re going to graduate from OMSCS, you should understand that no single setup works perfectly for everyone. Read the error messages and debug your environment yourself. Quizzes (19.31 / 20%): The quiz questions mainly test whether you watched the lectures. They’re pretty challenging, but you get two attempts, so overall it’s fair. I’m a horrible test taker(Check Digital Marketing Review). Practicum Project (34.5/ 35%): You can form your own group, and finding teammates who match your working style is ideal. It’s pretty easy to earn a high score, and the workload can feel either very light or very heavy depending on your group dynamics. Overall, the points are easy to earn. Other (6 / 6%): These are survey points—easy to earn. Participation (5 / 5%): These points are also easy. Try to complete them early so you don’t have to worry about them later in the semester. Rating: 4 / 5Difficulty: 1 / 5Workload: 6 hours / week - lVaErvC+H+S2COrzPeOalw== December 23, 2025 fall 2025 [Digital Marketing](https://www.omscentral.com/courses/digital-marketing/reviews) Finished the course with an B, achieving a 83.71 % Background: Bachelor's degree in Computer Science from a university ranked \#350-400 out of 436 National Universities in U.S. News English is my second language (TOEFL score: 95/120) 1 year of experience as a full-stack developer and 6 months of experience in data analytics Overall: This is probably the only B I got in the OMSCS program. I got As in my other courses like GA, ML, AI, KBAI, etc. I took this class because I felt a bit burned-out and wanted an easier semester, but it turned out harder than I thought based on my background. The biggest challenge was the exams because they focused too much on remembering English words and terms. Since English is not my first language, the questions were long and hard to understand sometimes, even though I studied. Still, I don’t regret taking this class. It was well organized and helped me learn how people use computers and mobile devices. As a data analyst who builds machine learning models for medical systems, this class gave me good ideas about how to collect and use user data. Major-Case Reflection Assignments (20 / 20%): These assignments are interesting, and as long as you understand what the question is asking and answer it correctly, it shouldn’t be a problem to get 100s. Weekly Mini-Case Discussions (20 / 20%): Smaller than Major-Case, you only need to watch the lecture video and explain what you think about the question. It’s fun and helps you learn some real historical cases. Midterm Exam & Final Exam (22.28 + 21.43 / 60%): The weight for this is just too high, as the overall summary explains. I tried my best. Rating: 5 / 5Difficulty: 2 / 5Workload: 6 hours / week - FC25WM4yyLYkJyZFjWz6mg== December 22, 2025 fall 2025 [Data and Visual Analytics](https://www.omscentral.com/courses/data-and-visual-analytics/reviews) I’m genuinely surprised this a required course for the OMSA program. If Georgia Tech prides themselves on providing leading education, this course is certainly not living up to that standard. The content feels like a hodgepodge of loosely connected material, nominally centered on visualization, but without much depth or cohesion. The lectures are extremely broad and don’t align well with the assignments. The workload is lighter than in most other OMSA courses. The D3 assignment in Homework 2 is the only part that takes a bit longer. D3 is tedious to learn and I highly recommend completing D3.js Essential Training by Emma Sanders on LinkedIn Learning. It will significantly help in completing the assignments. Half of the course grade is based on a group project with at least five team members. I generally dislike group projects with people I don’t know, but ironically, this ended up being the most enjoyable part of the class. Advice for Taking This Course: - Take it later in your program. You’ll be better equipped to define a meaningful project once you have more context from other OMSA or OMSCS classes. - Form a mixed group. A team with both OMSA and OMSCS students will bring strengths from the analytical and the computer science areas. - Choose a manageable project. Pick something with a clearly defined goal and a dataset that can be obtained. Start with a simple idea - you can always add complexity later. - Find your group early. Be proactive. Try forming your group at the very start of the course (or even just before it begins). - Meet weekly and stay organized. Set an agenda, assign roles and tasks, and ensure at least one team member keeps the project on track. - Check the checklists! The course, and especially the project, is full of detailed “to-do” lists that can make you feel micro-managed to the n-th degree! If you want a good grade, be sure to complete every item on those lists. Rating: 1 / 5Difficulty: 2 / 5Workload: 10 hours / week - /Uu79+lLvUsTQmFQj8joqA== December 22, 2025 fall 2025 [Applied Cryptography](https://www.omscentral.com/courses/applied-cryptography/reviews) ## My Impressions of the Course This was my first course in OMSCS. I made a decent A. This review may be a slight outlier because my academic background influenced how I approached this course (I have a master's degree in mathematics). If you don't have a mathematics background, it can be a bit difficult to adjust to how this course flows, because it's essentially a mathematics course in the formalism. ### Good Points - The TAs were very helpful and prompt to answer questions. - I even got answers to questions outside of the scope of the course (for instance, a proof regarding the DES complement property). - The material was presented in a very understandable way with a references given in the weekly Ed posts for reading from the recommended texts. - The homework assignments were very interesting, for the most part (coding homework 2 being the outlier; I'll touch on that later). - Coding Homework 1, in particular, was a very nice balance of being possible to break without requiring too much knowledge to break. - The quizzes were a bit on the easy side, but at least kept me engaged and accountable to some sort of routine. - The exams were just the right level of difficulty, where the points I lost I could entirely blame on myself. ### Neutral Points - There was no discussion on the designs of any of the cryptographic primitives or schemes presented. - I understand that this course isn't about implementation and all of the associated quirks (like constant-time operations to avoid side-channel attacks, which are meddled with by compiler optimizations), but at least having an idea of what the tools *do* would have been interesting. - I would have been okay with references to the standards / specifications. - While readings were given from the texts for the material, I would have liked if there were more readings from the literature to go into deeper detail or to see additional aspects that might not have been considered. - "Communication Theory of Secrecy Systems" by Shannon, "New Directions in Cryptography" by Diffie and Hellman, "A Method for Obtaining Digital Signatures and Public-Key Cryptosystems" by Rivest, Shamir, and Adleman, and many more papers are absolutely foundational and should be known by anyone in cryptography. - And papers like "Mining Ps and Qs: Detecting Weak Keys in Network Devices" by Heninger, Durumeric, Wustrow, and Halderman are important for understanding that weaknesses aren't just about the schemes and models, but about how they're implemented and used. - There were a couple of lectures about scheme implementation issues, so I won't say that this concept was completely ignored. - Again, however, more references means more opportunities to learn\! ### Bad Points - If I had to nitpick, I think the worst part of the course was how slow the lectures felt. - However, this was easily dealt with by watching at 1.5x speed. - Another issue is that I wish it was easier to download the videos for offline viewing. - I had to use the developer console to monitor for .m3u8 and .mp4 files and use FFmpeg to download the .m3u8 files to .mp4. - Some videos were .m3u8, others .mp4, so I couldn't just search for .m3u8 or just .mp4. - FFmpeg command used: `ffmpeg -protocol_whitelist file,http,https,tcp,tls,crypto -i video.m3u8 -c copy -bsf:a aac_adtstoasc video.mp4` (here, video.m3u8 is whatever you saved it as) - Since each lecture was broken up into 15-20 3-10-minute videos, this was quite tedious. - Coding Homework 2 was a bit too trivial. - Unfortunately, this comes with the territory. - Anything "breakable" is either trivially so or requires more knowledge than this course can give in a single semester from the level that students are expected to enter at. - The one exception I can think of was Coding Homework 1's problem. - Instead of requiring students to break a scheme, giving students a chance to build something might be a good alternative. - Maybe using this as an opportunity to walk students through how to implement a secure scheme using publicly available Python 3 libraries would be better, since it's a *very* small portion of a student's final grade. ## General Tips/Information - You'll want to be comfortable with reading and writing proofs, analyzing *what* a statement and proof are telling you mathematically, and have a decent grasp of discrete mathematics (elementary number theory, basic combinatorics, discrete probability). - If you have time before starting the semester, check out [MIT 6.042J (Math for Computer Science)](https://ocw.mit.edu/courses/6-042j-mathematics-for-computer-science-fall-2010/). - This has basically all of the mathematics you'll need. - Pay close attention to definitions. Remember them, internalize them. - This means taking the time to understand both the formal and conceptual meanings. - Use the proofs in the videos as templates for how you should write your solutions in the written homework and exam problems. - I highly recommend that you learn LaTeX so you can typeset notes and solutions. - Exams will require typing your solutions in some way, so being able to render your solutions to PDF using LaTeX will be helpful for readability. - You'll want to have a local installation for rendering your LaTeX to PDF, because Overleaf (or any other web-based editor) are not allowed during exams. - I used VS Code with texlive in WSL2 on Windows 11 and it worked just fine. - The lowest written homework grade and lowest quiz grade are dropped at the end. - Note that coding homework and exam grades are *not* dropped. - The grades are weighed as follows: - Quizzes: 15% - Written Homework: 15% - Coding Homework: 5% - Midterm: 30% - Final: 35% - There is a curve applied at the end, but the default grade intervals given in the syllabus are: - 80% \< Grade \<= 100% is A - 60% \< Grade \<= 80% is B. - So on for each 20% interval below. ## Homework Tips/Information - Most of the homework problems were about breaking a proposed scheme or (rarer) building a secure scheme using cryptographic primitives. - For the problems that ask you to build a secure scheme, you're not generally expected to prove that they're secure from base principles. - Instead, you just cite the relevant results from the lectures. - Make sure to pay attention to the resources your attacks use. - For written homework, make sure to use Gradescope's labeling feature to label which pages correspond to which problems. - You'll lose points if you don't mark the pages\! - Written homeworks are assigned every other week with one-week deadlines; there are a total of two coding homeworks, each with two-week deadlines. - The coding homeworks used Python 3 and were actually very easy. - The first coding homework took about an hour of coding and writing the report, but I had the advantage of having implemented the cryptographic tool used in the problem in C++ prior to taking the course. - A couple of hours of sitting with the RFC and realizing there's only a small part of the specification that's actually the crux of the weakness of the scheme should be enough to figure it out. - The second coding homework was absolutely trivial. It took about 15 minutes, and that includes running the code. - My overall homework grades: ~99% for written, 100% for coding. ## Quiz Tips/Information - The quizzes are very short and easy. - The answers are either verbatim lines from the videos / slides or can be easily deduced in one step. - You do need to pay attention to the questions. - If you're like me, you may misread a question and answer it incorrectly as a result. - For the first half of the course (through the midterm), quizzes test material from the previous week. - For the second half of the course (after the midterm), quizzes test material from *that* week. - Don't let the switch up catch you off guard. - I think this should have been better communicated (or should have remained consistent). - My overall quiz grade: ~97%. ## Exam Tips/Information - All exams are open notes but closed internet (besides a few links they whitelist). - I suggest having everything they allow you to use downloaded and ready to go on your computer (slides, the main texts, and external notes they may provide), even though they whitelist the links. - I felt much more comfortable knowing that I wouldn't have to open extra tabs in my browser and wait for them to load. - Use the quizzes as study material for the multiple choice portions of the exams, and use the written homework as study material for the written portions. - The multiple choice questions felt like they could have been alternative quiz problems. - The written portion of the exams tended to require a bit less insight than the written homework problems in the sense that it was much easier to see what you needed to do to solve them. - Don't rush, there's more than enough time (2 hour time limit). - Most of the points I lost in this class were on the exams because I didn't use the time as wisely as I should have. - My main issue was writing my general idea of an attack but forgetting to return to the problem to fill in the details after moving on. - Don't make this mistake; reread your solutions thoroughly before submitting. - Just like with written homework, you have to label which pages correspond to which written problem from the exam when uploading to Gradescope. - My exam grades: ~92% for midterm, ~86% for final. **My overall grade:** - 92% (raw score from the grade calculator provided by the staff) - A (letter grade) Rating: 5 / 5Difficulty: 2 / 5Workload: 7 hours / week - y95bmX+tFh3XCTGPOgZ78A== December 22, 2025 fall 2025 [Reinforcement Learning and Decision Making](https://www.omscentral.com/courses/reinforcement-learning-and-decision-making/reviews) RL is my 6th course at GT (AI/AI4R/ML/CV/RL). I got an A. I felt as though the course had the following issues: - The readings are pulled from a free online book and quite long, covering several topics that aren't pertinent to the projects. Likewise the required lectures are not useful for the projects beyond week 2-3; most students recommend watching a different set of lectures (David Silver). Personally, I didn't find the supplemental lectures or office hours useful. I ended up skipping the readings and lectures after the first few weeks. - The environments take a long time to run (e.g. \>3 hours); this means you have relatively few attempts to modify hyper-parameters which is challenging because there can be 1-2 dozen parameters to tinker with (and there is no working set of parameters supplied). - There is little to no 'hands-on' explanatory material. For example, there is little to no guidance on what kinds of diagnostics to use when trying to find a working set of hyper-parameters, and no discussion of how to interpret the results of those diagnostic measures. A short (time-lapsed) example where the presenter walks through finding a working set of hyper-parameters by examining some set of diagnostics on a problem they aren't already familiar with would have been informative. - As with ML & DL, the feedback comes late (6-8 weeks into the program), is infrequent (4-5 week periods), last-minute (prior report's feedback arrives 1-2 days before the deadline of the next project), and is often very brief, e.g. ~30-50 words per 8-page report (RL). I have never lost points for being incorrect (although I likely am), but only for omitting required material. The requirements documents are lengthy (\>7 pages) and the (graded) requirements are not always condensed into the 'requirements' section. - The final environment is not well-constructed; it's a 90s-looking game that runs at 10 FPS on modern hardware, and only on Intel CPUs. If you have a non-intel processor you will need to rent a computer. The school's PACE cluster may be available, but seeing as the project's assigned at the end of the semester (and around Thanksgiving in the fall), you'll likely be competing heavily with other students for access. - The final (MCMA) had little to do with the projects which dominated the time I spent on this course. I got a little above average, which was a bit below 50%. If you're dying to do well, review the (later) lectures and skip the textbook. I know more about RL after taking the course, but apart from the credential your time may be better spent doing personal research; the David Silver lectures are free, as is the Sutton & Barto textbook. I liked the OpenAI 'Spinning Up' explanations (e.g. for Proximal Policy Optimization \[PPO\]). Rating: 1 / 5Difficulty: 4 / 5Workload: 24 hours / week - Jlk0Gmfu1LnHpUt+1kQVyQ== December 22, 2025 fall 2025 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) Background: I graduated in Fall 2024 with a BS in CS at a similarly ranked school. I took Operating Systems there but had to drop the course. This is my first OMSCS course and I am currently work in Devops/Infra. This is the only course I took this semester. I got an A in the course. Overall, this was a great course, and a great introduction to OMSCS. The lecture content was interesting and presented in an easy-to-understand method. The lectures were split into 20 or so short videos and some quizzes to accompany them. This made it easy to rewatch parts of the lecture content I had trouble understanding, as I just needed to find the accompanying video. The material itself was not too difficult to understand, however my background definitely helped me in this regard. The readings were also interesting, and lecture content goes over their important concepts in good detail. The projects were the real fun portion of the course. I enjoyed every project and learned a great deal from each. They are not OS-specific projects, but deal with network programming, and helped me understand some of the concepts we covered in lecture(synchronization, IPC, gRPC). Projects 1 and 3 were in C, and 4 was in C++. I was comfortable with both so it was never an issue for me, but if you aren’t familiar, it might be difficult to pick up quickly. Overall I probably spent around 40 hours per project, and got full credit on each of them. Make sure to read Piazza posts and the Slack channel for tips, and don’t be scared to ask questions! The test cases weren’t particularly difficult to pass, and you have plenty of submissions. Any test case that fails gives you nice error messages that help you understand where you went wrong. The exams were mostly multiple-choice with some matching. I found that they were heavily based on memorization, and the projects don’t really help with the exams. Make sure to understand the lectures thoroughly and use lecture notes provided online to fill in any gaps. Be sure to ask in Piazza or Slack as well. Overall, I found the exams relatively easy. In general, this class helped me learn so much more about what the role of an operating system is, and made me a far better programmer regarding managing dynamic memory and multi-threaded applications. I learned so many things in this class! It is hard to put in words just how much I learned. If you like low-level programming and want to learn about the intricacies of the machines we take for granted, take this course\! Rating: 5 / 5Difficulty: 3 / 5Workload: 15 hours / week - Qhteq7WngCJs5IrUJuNRwg== December 22, 2025 fall 2025 [Database Systems Concepts and Design](https://www.omscentral.com/courses/database-systems-concepts-and-design/reviews) This was my first course at OMSCS, and I chose to take it despite the not-so-great reviews. I was pleasantly surprised by the experience. For context, I work as a data specialist at a small institution and come from what I would call a flawed CS education, so even though I completed a CS bachelor's degree, I consider myself much closer to a career switcher than a traditional CS student. The class is well organized with a clear grading breakdown: Four exams, each worth 12.5% (50% total) A three-phase final project worth approximately 35% Participation worth 15% Course Components Lectures: The lectures are pretty good and cover everything you need to know about database systems fundamentals: Relational Algebra and Calculus, Normalization, SQL basics, ER design, Relational Mapping, etc.. They do a good job of preparing you for the exams. There are also methodology lectures that clearly explain what's expected for each phase of the course project. Exams: The exams were fair, though attention to detail is VERY important (I can't stress this enough). Please read each question carefully (multiple times if necessary). Practice exams are invaluable for preparation. If you can complete the practice exam without looking up the answers, you should perform well on the actual exam. Project: This is the most variable component of the course, as your experience will depend heavily on your group. I was fortunate to have an amazing team, and everything went smoothly, making the workload quite manageable. However, I can easily see how a difficult group dynamic could make the project extremely challenging. Be proactive early in the semester to find a strong group. While you can't predict who might drop, aim to form a team with diverse skills. Ideally, someone experienced with databases (both conceptual design and SQL), someone with backend expertise, and someone with frontend skills. Yes, frontend skills. The Project is a full-stack web application. Grading Expectations This course is generally considered an easy B but a challenging A. There appears to be no curve. I scored in the 90s on everything and earned an A (94%). If you struggle on even one exam (and the average on the final was in the 70s) an A becomes difficult to achieve. Keep this in mind before registering; I'm providing this as helpful information, not to discourage you. Final Thoughts Overall, I think this is an excellent course. I highly recommend it if you've never taken a database class, love databases, or want to solidify your understanding of database fundamentals. However, this course may not be ideal if you're seeking advanced database topics, looking for an easy A, or prefer to avoid group projects. Rating: 4 / 5Difficulty: 3 / 5Workload: 15 hours / week - PwTXmUqnoUMXfduKETMS/A== December 22, 2025 fall 2025 [Machine Learning for Trading](https://www.omscentral.com/courses/machine-learning-for-trading/reviews) My background: first semester in OMSCS, CS undergrad, and 5 yoe as a software engineer. No ML or AI knowledge prior to this course. This course was awesome. The lectures were interesting, the projects were well-defined and fun to work on. I would recommend everyone take this course. It's the perfect intro to ML concepts. My only tip is to make sure to start assignments early, especially the final 2 projects. This course does use a lot of Python and Numpy. I have no professional experience in Python and had to re-learn a lot of it. Really not a big deal if you know how to code in any other language. Rating: 5 / 5Difficulty: 3 / 5Workload: 15 hours / week - PwTXmUqnoUMXfduKETMS/A== December 22, 2025 fall 2025 [Human-Computer Interaction](https://www.omscentral.com/courses/human-computer-interaction/reviews) My background: first semester in OMSCS, CS undergrad, and 5 yoe as a software engineer. This class was a great intro into HCI and the OMSCS program. I am not the best writer so the amount of written assignments almost scared me away. The assignments have clear directions and even as a weak writer you are basically guaranteed an A as long as you clearly follow the instructions. The group and individual projects are basically the same: practicing the design lifecycle using strategies that are well-covered in the course material and writing A LOT about it. Make sure to follow the directions closely and include everything they ask for. Overall, group projects put you at the mercy of your teammates. Don't leave your group up to chance: pick your team early to find proactive students to secure your A. I finished the class with an A but the team project almost sent me down to a B as most of my teammates didn't follow the directions and one didn't do anything. Rating: 4 / 5Difficulty: 3 / 5Workload: 15 hours / week - FuW7Lf2BVGTKYArYj7f7ew== December 22, 2025 fall 2025 [Artificial Intelligence](https://www.omscentral.com/courses/artificial-intelligence/reviews) This class provides a broad overview and introduction to topics in Artificial Intelligence. Because of the broad nature of the class, most topics to not build on what came earlier in the class. The first half of the class covered more traditional applications of artificial intelligence, such as search, game playing, and constraint satisfaction. The second half of the class covered probability, Baysian networks, and deep learning. The last time I took a probability course was many, many years ago and my knowledge was not adequate for the second part of the class and resulted in a frustrating experience. The class was well run and the TAs were active in the forum. While I didn’t enjoy the class, I did learn a lot and developed a better understanding of the AI buzzwords that are popular now. Rating: 3 / 5Difficulty: 4 / 5Workload: 15 hours / week - FuW7Lf2BVGTKYArYj7f7ew== December 22, 2025 summer 2025 [Introduction to Information Security](https://www.omscentral.com/courses/introduction-to-information-security/reviews) There was nothing to work on for the first week of class. I made use of the extra time by learning how to use Wireshark more effectively. If you can learn how to filter and use the tool, it will help a lot with the Man in the Middle project. This class had no exams or quizzes; it was all projects. The hardest part of this class is the constant pressure of a new project due every week, especially if you are not familiar with the topic that week. Compared to classes with more traditional programming projects it can be frustrating. There often isn’t the ability to make incremental progress, you either get the solution or you don’t. Overall, I enjoyed the class. If taking in the Fall or Spring the relatively light workload would pair well with another class. Rating: 3 / 5Difficulty: 2 / 5Workload: 12 hours / week - sO8OJlQ/P8sVDM5eftGHRA== December 22, 2025 fall 2025 [Network Security](https://www.omscentral.com/courses/network-security/reviews) tl;dr - Take IIS and skip this course. IIS is a much better course overall. NS is simply not worth your time or money. I have a lot to say about this course, but I'd rather keep this short and just hit the highlights. I'll start with the good and say that the TA's are great and helpful. Truly the one good thing about this course. Second, the malware section of this course is better IMO than the one in IIS. I think they should scrap NS, use the malware section from NS for IIS, and call it a day. I felt NS was a colossal waste of time. I only had to spend about 5 to 6 hours each week to get an A. The material is ancient by cybersecurity standards and references material that was published before I even started working in the industry. This isn't to say that information can't still be correct if it's old, but technology has changed so much since a lot of this course was written that I frequently struggled to find the relevancy. The projects are a mix between okay and outright terrible. I think the biggest letdown was the ML project. The IIS ML project did feel a little forced into the course, but at least you learned about encodings, training and testing, and fundamentals on how ML works. In this course you get to add some python to a tool that the professor helped author back in 2006! That's it. That's your ML project. My two cents is this: do not take this course. GATech should seriously consider either reworking this course or scrapping it altogether. It's a waste of students effort and money to have something in a graduate program that I think barely passes as undergraduate. I highly recommend Advanced Topics in Malware Analysis if that's your thing. Otherwise, just take something else, anything else. AIES was better. Rating: 1 / 5Difficulty: 1 / 5Workload: 5 hours / week - ipe1i/snfsp+HDoZP/0IFw== December 20, 2025 summer 2025 [Deterministic Optimization](https://www.omscentral.com/courses/deterministic-optimization/reviews) *Taken Fall 2025* The reason I am leaving a review is because I saw a recent negative post about this class and wanted to chime in. Firstly, as someone who enjoys math, I really enjoyed this class. I think the class is well-structured and the homework reinforces the materials since it forces you to apply course concepts. You learn to how to model problems as optimization problems and then methods for solving said problems. It was interesting and felt very practical. I didn’t think the material was hard, but it definitely assumes some familiarity with derivatives and linear algebra. Secondly, I’m not sure if there was a curve at all. My assumption was that there was no curve. If there was one, then it was not mentioned at all by staff. I managed to get an A without any curve. Getting an A is definitely doable, but it is stressful because of how heavily weighted each exam is. I firmly believe that if you did the knowledge checks and practice exams, like really really studied them, then you’d be well-prepared for the exams. Lastly, the material is definitely relevant. Linear programming might not be prominent in everyday life, but some concepts definitely appear frequently. If your job is to model problems and solve them, then this course is relevant. If you’re in the ML space, then you’re bound to encounter optimization problems since the goal is to either minimize error or maximize performance. See Andrew Ng’s lectures on regression/classification and you’ll see the importance of optimization. Rating: 5 / 5Difficulty: 2 / 5Workload: 8 hours / week - mWlYV8RYUV9ANY+ovth3FQ== December 20, 2025 summer 2025 [Reinforcement Learning and Decision Making](https://www.omscentral.com/courses/reinforcement-learning-and-decision-making/reviews) Actually took course in Fall 25, but that option wasn't listed on form. Giving the course a 1 because the same feedback is given by almost every student and no attempt has been made to fix it. My feedback is pretty much the same as every other student. Lectures are old and disjoint from projects. No need for the final to be as hard as it is and very taxonomic/unrelated to projects. Ultimately not much better than just seeking out and doing RL projects yourself. For a grade I got near perfect scores on the first three projects and then phoned in the last project and the final. That was enough to get a B, which is all I needed to get reimbursed from my company for the course. Median on the final was ~48%. Rating: 1 / 5Difficulty: 5 / 5Workload: 25 hours / week - KU1E6SWndsiNMKo6qjvF0w== December 20, 2025 summer 2025 [Deterministic Optimization](https://www.omscentral.com/courses/deterministic-optimization/reviews) This course sucks in the way that it forces curve. Only x % got A no matter what. I don’t agree with some comments here praising the course design. It’s pretty much all about linear programming and old school stuff and to be honest, it has almost 0 value in real practice. Rating: 1 / 5Difficulty: 2 / 5Workload: 5 hours / week - u3nsnLbC8JcfIhZUgs8zlg== December 19, 2025 summer 2025 [Introduction to Health Informatics](https://www.omscentral.com/courses/introduction-to-health-informatics/reviews) Fall 2025 First half of the course with labs, quizzes and lecture videos were great. My average time spent was about 5 hours/week Second half of the course with the group project was a disaster because my teammates were not familiar with git and web development plus not willing to spend the time to learn them. Ended up doing the group project myself entirely. I heard that other people enjoyed their group project because they had amazing teammates. Your group project experience really depends on your teammates. The course would have been a lot better if I had better teammates. Doing the course project as a solo was prohibited. Choose your teammates wisely. Pick those who have actually web dev/full-stack experience. No amount of gatech courses taken would be a sufficient substitute of that experience. I have heard horror stories of group projects in gatech previously. This time I am the survivor who experienced it first hand. Rating: 5 / 5Difficulty: 1 / 5Workload: 20 hours / week - Y//78ivuAYK34qoqqIUJsA== December 18, 2025 summer 2025 [Introduction to Computer Vision](https://www.omscentral.com/courses/introduction-to-computer-vision/reviews) ## Actual term: Fall 2025 Final grade: A I'm a CS undergraduate and even though I'm not exactly new to computer vision (as I've already taken Deep Learning, and learnt a bit of geometric vision a few months ago) I'm far from actually knowlegeable in the subject. My overall experience was positive. There is a ton of material and a ton of work since the assignments require knowledge about the algorithms, implementing them from scratch, and lots of tuning to make them work, at least for grading. Assignment 3 in particular was the most demanding and lengthy, and it was the only assignment where we were given a 2-day extension. I felt kinda burnt out after this assignment and "slacked" in the next two (I did everything except the extra credit sections). The final exam was comprehensive but fairly reasonable in difficulty. It's open everything (except for direct answers, especially from LLMs) and multiple-choice. It is actually just an excuse to review the material (and they say so). I cannot comment on TAs or the instructor as I never needed them. Everything was covered in the lectures (with an additional independent reasoning), READMEs and FAQs. I don't understand people complaining about unclear expectations, rubrics, etc. They tell you everything you need to know, and expect you to study just a bit for yourself (as should be expected). The only parts where I was not given credit where the sections I didn't answer, and the only parts where I was given partial credit were sections that I intentionally didn't want to answer more precisely (especially those requiring microscopic fine-tuning). I did Action Recognition for the final project and it felt like an additional problem set (and it actually was an extra problem set many years ago) with an extra workload since you have to create your own (numeric) dataset out of some videos, but the algorithm itself is really straightforward. I think that this course is only a must-take course if you're really serious about computer vision and think that deep methods can't solve everything. Rating: 5 / 5Difficulty: 3 / 5Workload: 18 hours / week - LrS4aqhyfWY1FWNImRt0sw== December 18, 2025 fall 2024 [Graduate Introduction to Operating Systems](https://www.omscentral.com/courses/graduate-introduction-to-operating-systems/reviews) Non-CS STEM major (Electrical Engineering), no coding experience in the past 5+ years. Took GIOS as the first class in the program. This was a tough class that consumed a lot of time, especially because I had to learn C, C++, and gRPC on the fly. However, this class teaches you a lot about how operating systems work and makes you a strong (or stronger) C programmer by the end. I would highly recommend this class if you are willing to learn and are prepared to put in the time. Project 1 (Pr1): I spent the most time on this project because I had to learn how to code in C and read Beej’s Guide to Network Programming. This project is broken into four parts. Each part is designed to help you learn what is needed for the subsequent part, and by the end, you can create a multi-threaded getfile library. I spent a significant amount of time compared to others, likely because I had no prior C experience and hadn’t been coding in recent years. • Part 1: 10 hours • Part 2: 10 hours • Part 3: 80 hours • Part 4: 80 hours *** Project 3 (Pr3): For this project, I spent a lot of time thinking about the design, referring to comments on Slack to understand how other students were approaching the problem, and asking questions to verify my understanding of the project and my design. Writing the actual code was less time-consuming compared to Project 1. • Part 1: 20 hours – This part was simple and helped me get familiar with the CURL library. • Part 2: o 20 hours – Researching and coming up with the design. o 40 hours – Writing code, implementing, and debugging. *** Project 4 (Pr4): This was the hardest project for me, even though many others thought it was the easiest. It may have been easier for students who already had exposure to gRPC or something similar. If you have time after finishing Project 3 and before starting Project 4, I highly recommend spending some time learning about gRPC—it will help a lot. • Part 1: o 20 hours – Learning how gRPC works and understanding examples. o 10 hours – Writing the actual code. • Part 2: o 40 hours – Figuring out how the overall library was intended to work based on the provided codebase. While I had to do this for all the projects, this one was particularly hard because it was complex, and there were so many different .ch files to read and fully understand before I could grasp how the DFS was intended to work. o 30 hours – Writing the actual code. *** Midterm Exam: The midterm wasn’t too hard. Just keep up with the lectures and make sure you thoroughly understand the practice exam. *** Final Exam: The final exam was much more challenging. The amount of material covered on the final is roughly twice what’s covered on the midterm. By the time I finished Project 4, I was six lectures behind, and I had only about 10 days to prepare for the final. Trying to cram all the material into a short amount of time, like a week, was brutal. Since I calculated that I only needed 55+ points to achieve 84% or higher overall, I took the exam without adequate preparation—and that was a big mistake. I spent several days anxiously waiting for the final exam grade because I thought I had bombed the test. *** Final Thoughts: I agree with the strategy of starting projects as soon as they are posted. As long as you put in the time, refer to the Slack channel for clues when you get stuck, and ask questions, you should be able to score 100% on all the projects. If you get 100% on all projects and score at least the median (~75%) on the exams, you should be able to earn an A, which typically has a cutoff of 81%-84%, depending on the class average. If I had to retake the class, I would allocate 1 hour per day to studying or staying up to date on lectures, even while working on projects. Cramming everything before the midterm and final because I dedicated all my energy to getting perfect scores on Gradescope was not a smart idea. Since the three projects account for 45% of the total grade and the two exams account for 50%, allocating time to exam preparation has a better ROI for achieving a good grade. *** My Results: I ended up with a grade well above the curve for an A (82% for Fall 2025). • Projects: Full scores (~100%) on all three. The class median was also nearly 100% for all projects. • Midterm: Scored in the 75th percentile, well above the median. • Final: Scored in the 50th percentile, around the median. *** Rating: 5 / 5Difficulty: 4 / 5Workload: 25 hours / week - ZduXZVe+NcBIRDua2dy92A== December 18, 2025 summer 2025 [Machine Learning](https://www.omscentral.com/courses/machine-learning/reviews) This review is for Fall 2025 term. Just finished the class with an A. It has been a tough class, probably the most laborious and time-consuming among all I’ve taken so far (see below). One piece of advice to those who are going to take this class: have a LOT of time on hands to spend on this class. No matter what your background is, if you have time to spend on this class you are likely to succeed. Also, when you write your reports, it helps to have a dedicated “Hypotheses” section with a few numbered hypotheses that are drawn from the course material or papers (explicitly sighted) and then in the Results/Conclusion sections you explicitly accept or reject each of these numbered hypotheses. Background: 7th class in the program (after AI4R, KBAI, ML4T, AI, DL and CN). The material in ML4T, AI and DL was very useful as a pre-courser for ML - most items in this course looked familiar which helped a lot. Prior to that – no/minimal CS but some STEM academic background (from about 20 years ago). I do have some experience with academic writing and LaTeX, both the previous academic background and from current work. Other than that, demanding full-time on-site job, family and other obligations. Taking the program mostly for self-development, not for career change (although – who knows nowadays). I value the courses I take as the ratio of how much new I learned vs. the amount of time and stress it took. For this class, the denominator goes to infinity whereas the numerator, while large, is finite. Hence, it was not my favorite class (so far, the best class for me was AI4R, and by far the worst – KBAI (please do not waste your time with this class)). The good: - Professor LaGrow and all teaching staff do their best to encourage the students. You may (and most likely will) feel miserable at times but they don’t want you to. With the number of extra points, reviewer response, etc. anyone who spends the proper time on this course can succeed. - The material is quite interesting. Maybe not the very cutting edge but essential. - I obtained (or started obtaining) a very useful skill: using AI code generating tools to produce the code that does the desired analysis. I would not be able to write all the code for all the analysis by myself – nor apparently this is needed any longer. Not so good: - I felt that the amount of material was overwhelming. With its breadth, it was not possible to dive deep enough. Every 3 weeks a super large topic was covered, and in these 3 weeks, one had to (preferably) understand what’s going on, write (or generate) bunch of code, run it on two very different datasets (one of which is huge and super noisy), design and run your experiments that should test a few dozen things and then write an 8-page report. - The course puts an emphasis on academic writing. Although undoubtfully an important skill (plus helps to organize the subject knowledge), I believe in this case this emphasis was excessive. I’d much rather prefer to understand the subject matter deeper. - There is a lot of debate on the quality of the lectures. Some love this format, some hate it. I would have been OK with it if the lectures were not so long. With the number of things to do for the course, I could not afford to spend several hours a week listening to the lectures. It feels that the same could have been said in a more concise manner. As many students complain, the report grading feels random. My grades were 89, 89, 62 (+19 recovered in reviewer response), 101 but the structure of report 3 mimicked that of 1 and 2. The main complaint of Report 3 grader was that there was no a dedicated section with the “numbered” hypotheses (although they were formulated in the Methodology and Data sections of the report). Most likely the need for the separate section was discussed in the OH (that I mostly could not attend) but there was no such requirement in the project description or the FAQs. What I’m trying to say is that I had no feeling at all about what grade I was going to get for the reports (I personally felt that my report 3 was stronger than 1 and 2). All in all, I’m not regretting taking this course, just wish it was not taking ALL my time (and more). Rating: 4 / 5Difficulty: 5 / 5Workload: 30 hours / week - 8/lglYFHPFGhVYhCsoaRaw== December 17, 2025 spring 2025 [Introduction to Graduate Algorithms](https://www.omscentral.com/courses/introduction-to-graduate-algorithms/reviews) This class is very exam heavy, so go in knowing exactly what you’re signing up for. Exams are 90% of the grade, while the formatting/logistics/content quizzes are pretty easy and make up the remaining 10%. Even if the homeworks are optional, do them. They’re one of the best ways to understand how the exams are structured and what level of precision is expected. Also, attend office hours. They help way more than you’d think. If you believe you were graded incorrectly, submit a regrade request. A lot of students don’t do this out of laziness. Just be aware that the entire question gets re-reviewed, so if they find an additional mistake you might lose points too. Still, if you’re confident, it’s worth it. You genuinely need to study hard for this class. You can’t rely on Chat GPT or shortcuts to pass cause this course really tests understanding. Proctoring is also very strict, so follow every instruction carefully or you’ll risk unnecessary penalties. This class is doable, but it requires serious effort. No slacking. It honestly feels like the ultimate boss of OMSCS. For reference, I got 35/60 on the first exam, 49/60 on the second, and 42/60 on the third. If you do poorly on the first exam, don’t get discouraged-it’s very possible to recover if you adjust and study harder. One final warning: formatting and wording matter a LOT. The TAs expect answers in a very specific format, and being even slightly unclear can cost you points. One wrong word can mean deductions, so be extremely precise and explicit in your exam responses. Overall: tough class, high workload, but passable if you hustle and put in the work. \-NP Rating: 3 / 5Difficulty: 5 / 5Workload: 30 hours / week