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In this program, you’ll gain an advanced understanding of topics such as artificial intelligence, cybersecurity and big data, while strengthening your skills through technical projects. [Learn more](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/#program-detail) Quick facts  Next start date: 05/18/2026 ***  Total classes: 10  Weeks per class: 7\.5  Total credit hours: 30 Overview Overview - [Overview](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/#program-intro) - [Details](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/#program-detail) - [Courses](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/#program-courses) - [Careers](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/#program-careers) - [Admissions](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/#program-admissions) - [Accolades](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/#program-accolades) - [Tuition](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/#program-cost) [Apply now](https://webapp4.asu.edu/dgsadmissions/Index.jsp?program=GRES&plan=ESCOMSCMCS&campus=ONLNE&subplan=null&term=2264&session=REG) [Request Info](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/#program-rfi) ## Prepare for in-demand high-paying jobs with a computer science master’s Organizations across industries from health care and business to engineering and education rely on those with computer science knowledge and skills. According to the U.S. Bureau of Labor Statistics, employment for computer and information research scientists is expected to grow by 23% from 2022 to 2032, which is much faster than average for all occupations. Earning a Master of Computer Science is a step toward advancing your career in a lucrative field. Computer and information research scientists made a median annual salary of \$136,620 in May 2022, according to the U.S. Bureau of Labor Statistics. ## The skills you’ll develop in this master’s program This Master of Computer Science program is designed to build your knowledge about a range of topics from designing software for networks, graphics and database systems to integrating computer science with biology, geography, public health and more. Upon graduation, you’ll have a variety of skills, including: - Designing and analyzing computers. - Implementing computational processes. - Improving software reliability, network security and information retrieval systems. - Inventing next-generation computer systems, computer networking, biomedical information systems, gaming systems and more. - Transferring and transforming information. Read more ## Tailor your studies to fit your career goals In this program, you’ll create a customized plan that aligns with your career goals. A majority of your courses will be electives, giving you the opportunity to explore your interests in a variety of topics, such as artificial intelligence, blockchain and software engineering. Interested in delving deeper into specific areas of computer science and gaining career-relevant skills? Check out the two available concentrations: - [Big data systems](https://asuonline.asu.edu/online-degree-programs/graduate/master-big-data/). - This concentration focuses on creating scalable systems to manage, interpret and analyze large amounts of data. You’ll also learn how to draw conclusions from data that enables organizations to make informed decisions. - [Cybersecurity](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-cybersecurity-mcs/). - In this concentration, you’ll gain the skills needed to safeguard information systems, develop solutions and mitigate risk.  ### Professional certification and nondegree enrollment opportunities 1. As a nondegree-seeking graduate student, you can take master’s-level computer science courses without being admitted to the program. This provides you the opportunity to establish a high graduate GPA, try out courses, meet the English proficiency requirement or earn a professional certification credential. Those who complete three courses with a cumulative GPA of at least 3.00 after the first attempt can use this GPA and the credit hours earned when applying for the Master of Computer Science program. You must also meet all prerequisite requirements to be admitted. [Learn more](https://goto.asuonline.asu.edu/mcs-professional-certifications/)  ### Will my diploma say ‘online’? No, Arizona State University’s diplomas don’t specify whether you earn your degree online or in person. All diplomas and transcripts simply say “Arizona State University.” ## Earn a Master of Computer Science online from anywhere. Watch video ## Computer science master’s courses You’ll choose one course in each of three primary areas of study: theoretical foundations, systems and applications. You’ll also take several elective courses on topics ranging from statistical machine learning and mobile computing to data mining and information assurance. *** Foundations ### Bio-Inspired Computing *** [View course details]() Foundations ### Foundations of Algorithms *** [View course details]() Foundations ### Knowledge Representation and Reasoning *** [View course details]() Systems ### Advanced Computer and Network Security *** [View course details]() Systems ### Applied Cryptography *** [View course details]() Systems ### Distributed and Multiprocessor Operating Systems *** [View course details]() Systems ### Information Assurance and Security *** [View course details]() Systems ### Mobile Computing *** [View course details]() Show more ## The roles a master’s in computer science prepares you for This program can give you a leg up and advance your career in a variety of technical disciplines. Upon graduating, you’ll be equipped to pursue career paths ranging from software engineering, cloud computing and machine learning information security to application development, software QA and web development. Roles you may pursue include, but aren’t limited to: Computer network analyst Computer programmer Computer scientist Computer systems analyst Database administrator Information technology manager SEO specialist Software developer  ### Study with award winning faculty members in the field of computer science Of the 350+ faculty members in Ira A. Fulton Schools of Engineering, the majority have been honored with the highest awards in their fields. Faculty milestones include: - National Academy of Engineering members. - National Academy of Sciences member. - National Academy of Inventors members. - National Academy of Construction members.  ### Study with award winning faculty members in the field of computer science Of the 350+ faculty members in Ira A. Fulton Schools of Engineering, the majority have been honored with the highest awards in their fields. Faculty milestones include: - National Academy of Engineering members. - National Academy of Sciences member. - National Academy of Inventors members. - National Academy of Construction members. ## How to apply This program has a highly competitive admission process. ### Application deadlines Applicants with international credentials have an application deadline of six weeks prior to the selected session start date. All other applicants have an application deadline of four weeks prior to the selected session start date. This degree is offered in A and B sessions for fall and spring, and in C session for summer. You can view upcoming start dates in the [academic calendar](http://students.asu.edu/academic-calendar). **How to complete an application** - Submit online application and pay application fee. - Send official transcripts to ASU’s graduate admission services. - If needed, send proof of English proficiency. - If you’re not a U.S. citizen but are living in the U.S., send a copy of your U.S. visa to [gograd@asu.edu](<mailto: gograd@asu.edu>). - If you’re based outside of the U.S., select "JN" under Visa. For questions, call 1-844-353-7953 or email [mcsenrollment@asu.edu](<mailto: mcsenrollment@asu.edu> "mcsenrollment@asu.edu"). ### Admission requirements for computer science undergraduate majors You must have completed an undergraduate degree in computer science from an accredited university. Please review the necessary CS pre-requisite courses in the section below to confirm eligibility. **GPA requirements** A minimum cumulative GPA of 3.00 in the last 60 credit hours (last two years) of a four-year undergraduate degree. If your degree was completed in the U.S., it must be from a regionally accredited university. Applicants who have previously completed graduate-level coursework must have a minimum post-baccalaureate/graduate GPA of 3.00. **English proficiency** If all college degrees are from a country outside of the U.S., you may need to demonstrate [English proficiency](https://admission.asu.edu/apply/international/graduate/english-proficiency). Note that the MCS degree requires higher English proficiency scores. - TOEFL: 575 paper-based / 90 internet-based. - IELTS (academic version): 7. - PTE: 65. - Duolingo: 115. Don’t yet meet this requirement? If you complete the pathway with a 3.00 or higher, you’ll have demonstrated English proficiency. Click on the nondegree tab below to learn more. ### Admission requirements for non-computer science undergraduate majors **GPA requirements** A minimum cumulative GPA of 3.00 in the last 60 credit hours (last two years) of a four-year undergraduate degree. If your degree was completed in the U.S., it must be from a regionally accredited university. Applicants who have previously completed graduate-level coursework must have a minimum post-baccalaureate/graduate GPA of 3.00. **Math course requirements:** You must have two semesters of advanced math in Calculus I and Calculus II, as well as a background course in discrete math.\* Applicants with an undergraduate degree in a STEM field have likely completed the math requirement. \*Discrete math is not always a separate class at all universities. Taking a course that covers data structures and algorithms may also fulfill this requirement. If you’ve never done algorithms, you may not have the proper background for the program. **Pre-requisite course requirements:** To be eligible for this program, you must have programming knowledge in a variety of languages, including C/C++, Java, Python and HTML, as well as courses in calculus and discrete math. **CS course information:** **CSE 230: Computer Organization and Assembly Language Programming** - Register-level computer organization, instruction set architecture, assembly language, processor organization and design, memory organization, IO programming and exception/interrupt handling. **CSE 310: Data Structures and Algorithms** - Advanced data structures and algorithms, including stacks, queues, trees (B, B+, AVL), graphs and searching for graphs, hashing and external sorting. **CSE 330: Operating Systems** - Operating system structure and services, processor scheduling, concurrent processes, synchronization techniques, memory management, virtual memory, input/output, storage management and file systems. **Principles of Programming Languages OR Introduction to Theoretical Computer Science** **CSE 340: Principles of Programming Languages** - Formal syntactic and semantic descriptions, compilation and implementation issues, and theoretical foundations for several programming paradigms. **CSE 355: Introduction to Theoretical Computer Science** - Introduces formal language theory and automata, Turing machines, decidability/undecidability, recursive function theory and complexity theory. **CS competency exams** If you don’t have these topics on your transcript but have a strong understanding of them, you can take the prerequisite knowledge exams. If you complete the [exams](https://careercatalyst.asu.edu/programs/?college=Computer%20Science%20Graduate%20Programs) with the grade outlined in the respective syllabi, you’ll satisfy that prerequisite knowledge requirement. **English proficiency** If all college degrees are from a country outside of the U.S., you may need to demonstrate [English proficiency](https://admission.asu.edu/apply/international/graduate/english-proficiency). Note that the MCS degree requires higher English proficiency scores. - TOEFL: 575 paper-based / 90 internet-based. - IELTS (academic version): 7. - PTE: 65. - Duolingo: 115. Don’t yet meet this requirement? If you complete the pathway with a 3.00 or higher, you’ll have demonstrated English proficiency. Click on the nondegree tab below to learn more. ### Professional certification and nondegree enrollment opportunities As a nondegree graduate student, you can begin taking graduate-level computer science courses without being admitted to the master’s program.\* **Professional certification** If you’re not sure you want to pursue the full degree or only want to focus on a specific topic, you can earn a professional certification for ASU credit. To receive a professional certification, you must successfully complete at least three courses from that topic area with a grade of “B” or better. Available certifications include: - AI and machine learning. - Big data. - Cybersecurity. - Software engineering. [Learn more](https://goto.asuonline.asu.edu/mcs-professional-certifications/) about professional certifications. **General pathway** This pathway provides an opportunity to take a variety of courses as a nondegree-seeking student to explore topics or meet this program’s GPA and English proficiency admission requirements. Completing nine graduate credits with a “B” or better (3.00 GPA) will demonstrate English proficiency. Through this pathway, you can choose and complete any three 500-level courses that are part of the Master of Computer Science program as a nondegree-seeking student. The courses you complete with a “B” or higher, up to 12 credits, will apply to the Master of Computer Science if you’re admitted to the program within three years of completing the courses. [Begin your application](https://webapp4.asu.edu/dgsadmissions/Index.jsp?program=GRND&plan=ESMCSNONDG&subplan=&campus=ONLNE&osm=true) for one of the four professional certifications or the general pathway. The ASU graduate admission office will review the application and notify you by email if any additional steps are required upon admission. All official emails will go to your ASU student Gmail account. **Please note:** - If you don’t enroll in the semester in which you are admitted, you must submit a new application and pay the application fee. - Completing the pathway or professional certification does not waive the requirement for all applicants to the Master of Computer Science program to demonstrate mathematics and computer science topic prerequisite knowledge. See the admission requirements sections above for more information. \*If you do not have the prerequisite knowledge outlined in the master’s admission criteria for mathematics and computer science, you should be aware that you may not have the necessary background for graduate CSE courses and are enrolling at your own risk. You are responsible for acquiring that knowledge before and during the course. ## Top 25% of all accredited engineering programs in the nation The Ira A. Fulton Schools of Engineering is dedicated to providing a dynamic learning environment and supporting all students on the paths to their degrees. We’ve received numerous peer-reviewed programmatic honors from U.S. News & World Report. ### \#2 *** best online master’s in electrical engineering programs. ### \#2 *** best online master’s in engineering management programs. ### Top 5 *** for bachelor’s degrees awarded to underrepresented minorities (American Society for Engineering Education 2022). ### Top 10 *** best online master’s in engineering programs for veterans. Show more  ### Tuition calculator Use our calculator to estimate your full-time or part-time tuition fees for this program prior to any financial aid. Keep in mind that most of our students receive financial aid, which can reduce out-of-pocket costs. [Learn more.](https://asuonline.asu.edu/what-it-costs/financial-aid/) [Estimate tuition and fees](https://asuonline.asu.edu/)  ### Tuition calculator Use our calculator to estimate your full-time or part-time tuition fees for this program prior to any financial aid. Keep in mind that most of our students receive financial aid, which can reduce out-of-pocket costs. [Learn more.](https://asuonline.asu.edu/what-it-costs/financial-aid/) [Estimate tuition and fees](https://asuonline.asu.edu/) ## View the most commonly asked questions ### Do prerequisites need to be taken from ASU? We understand that many applicants have IT experience. To reduce the barriers to entry, ASU provides applicants an option to prove their computer fundamental understanding through prerequisite knowledge exams. Passing the proctored exam will provide completion of the prerequisite. [Learn more and sign up for the exams](https://careercatalyst.asu.edu/programs/?college=Computer%20Science%20Graduate%20Programs). ### Is there any credit offered for work experience in IT? No. Academic credit cannot be given for work experience in the field. ### Can completing professional certification coursework satisfy prerequisites? Completing professional certification courses alone does not waive a prerequisite, but completing the courses and working through the material can be an excellent way to prepare for the exams offered through [CareerCatalyst](https://careercatalyst.asu.edu/). ### Are letters of recommendation required for admission? No, letters of recommendation are not required. ### What is a statement of purpose? A statement of purpose should include your reasons for undertaking the graduate work and an explanation of your academic interests, including their relation to your professional goals. There is no specific length for a statement of purpose. A resume will be accepted as a personal statement. Students are welcome to submit a resume or a statement of purpose or both. ### How can I check the status of my application? You’ll receive email updates on the status of your application, so be sure to check your ASU email regularly for these notifications. You can also see your status by logging into my.asu.edu with your ASURITE ID and reviewing the section called ‘My Application Status.’ This section will display pending checklist items or an application decision. If you have questions on pending items, please contact us toll-free at 1-844-353-7953 or email [mcsenrollment@asu.edu](<mailto: mcsenrollment@asu.edu>). ### Do the MCS courses need to be taken in a specific order? No. You can take courses in any order. However, you must take one applications course, one systems course and one foundations course as part of the graduation requirements. You must also complete seven CSE elective courses. ### It says the program takes 18–36 months to complete. Can it be completed earlier than that? The completion time is based on the number of courses you enroll per semester. You must complete 30 credit hours to get your master’s degree. ### How much time can I expect to spend per week on class projects and assignments? These courses follow an accelerated format. As such, you should expect to spend 15–20 hours per week on each course. ### Can I transfer from online to on-campus while pursuing my Master of Computer Science degree? You’ll need to submit a new application to transfer your credits. If accepted, you can transfer up to 12 credits from an online program to the same on-campus program, as long as your grades are “B” or better. ### What is the total cost of the degree program? The total cost of the degree program is \$15,000, or \$1,500 per 3-credit course. There are no textbooks required for the courses and no additional fees. You’ll only be billed for the courses you’re enrolled in. ### Do I have to pay for the entire degree upfront? You only have to pay for the courses you are enrolled in. ASU also offers a payment plan, which provides you with the option to budget the payment of certain eligible university charges over several months within the semester. ### How do I get billed and when do I pay? Your bill will be displayed in the my.asu.edu portal. The payment deadlines for each session are also on the [academic calendar](https://registrar.asu.edu/academic-calendar). ### How do ASU students access the alumni network? Information about the ASU alumni network is available at <https://alumni.asu.edu/>. [Show less]() ## You might also be interested in ![Computer Science – Cybersecurity (MCS)]() Graduate #### Computer Science – Cybersecurity (MCS) *** Starts 05/18/2026 [Learn more](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-cybersecurity-mcs/) ![Graphic Information Technology (MS)]() Graduate #### Graphic Information Technology (MS) *** Starts 05/18/2026 [Learn more](https://asuonline.asu.edu/online-degree-programs/graduate/graphic-information-technology-ms/) ![Information Technology (MS)]() Graduate #### Information Technology (MS) *** Starts 05/18/2026 [Learn more](https://asuonline.asu.edu/online-degree-programs/graduate/information-technology-ms/) ![Computer Science – Big Data Systems (MCS)]() Graduate #### Computer Science – Big Data Systems (MCS) *** Starts 05/18/2026 [Learn more](https://asuonline.asu.edu/online-degree-programs/graduate/master-big-data/) [See all degrees](https://asuonline.asu.edu/online-degree-programs/) [Apply now](https://webapp4.asu.edu/dgsadmissions/Index.jsp?program=GRES&plan=ESCOMSCMCS&campus=ONLNE&subplan=null&term=2264&session=REG) Contact ![ASU Online]() *** ASU Online is dedicated to providing innovative, high-quality online education to students from across the country and around the world. - [Apply now](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/) - [Help Desk 855.278.5080](tel:1-855-278-5080) - [Enrollment 866.277.6589](tel:1-866-277-6589) - [enrollmentonline@asu.edu](mailto:enrollmentonline@asu.edu) ### Online Degrees [All Online Programs](https://asuonline.asu.edu/online-degree-programs/ "All Online Programs") [Undergraduate Degrees](https://asuonline.asu.edu/online-degree-programs/undergraduate/ "Undergraduate Degrees") [Graduate Degrees](https://asuonline.asu.edu/online-degree-programs/graduate/ "Graduate Degrees") [Graduate Certificates](https://asuonline.asu.edu/online-degree-programs/certificates/ "Graduate Certificates") [Nondegree 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Locations](https://www.asu.edu/about/locations-maps)[Jobs](https://www.asu.edu/asujobs)[Directory](https://isearch.asu.edu/asu-people/)[Contact ASU](https://www.asu.edu/about/contact)[My ASU](https://my.asu.edu/) [Copyright and Trademark](https://www.asu.edu/about/copyright-trademark)[Accessibility](https://accessibility.asu.edu/report)[Privacy](https://www.asu.edu/privacy/)[Terms of Use](https://www.asu.edu/tou/)[Emergency](https://www.asu.edu/emergency/) Manage my privacy settings × ### Bio-Inspired Computing ### About this course Bio-inspired computing methods are derived from information-processing mechanisms found throughout the living world. Bio-inspired algorithms are used widely across the field of computer science in areas such as optimization, robotics, artificial intelligence, software engineering, security and modeling. This graduate-level introduction to bio-inspired computing explores computational methods based on biological processes and how to apply them to solve computational problems. The course will cover computational algorithms, models and applications that are inspired from three primary areas of biology: evolution, immunology and social insects. You’ll also gain insight into cutting-edge applications of biology in computing. **Specific topics covered include:** - Applications: ant colony optimization (ACO) algorithms, trail following and network algorithms. - Applications: Negative selection algorithm, artificial immune systems and computer security. - Applications: Olfactory systems and similarity search. - Applications in software engineering and artificial intelligence. - Biological perspective on neurocomputing. - Biological underpinnings. - Current frontiers: Collective computation and swarm robotics. - Evolution. - Evolutionary computation and genetic programming. - Frontiers of bio-inspired computing. - Immunology. - Metabolic scaling: Predicting power consumption on chips. - Molecular computing: DNA storage technologies. - Search spaces and biased sampling, algorithms for recombination, selection and mutation. - Social insects. - Why AI is harder than we think. **Technologies covered include:** - Java. - Python. ### Required prior knowledge and skills This course will be very challenging, so learners are expected to possess the needed prior knowledge and skills and/or learn it and the necessary technologies on their own time. A prior background in biology isn’t required. **Proficient mathematical skills and theoretical understanding** - Basic probability, statistics and linear algebra. - Computer science knowledge, including data structures, algorithms and complexity theory. - Critical thinking and reading skills. **Strong application skills** - Ability to read and comprehend Python code. - Ability to read scientific literature. - Competence in computer programming. - Confidence in executing Python assignments. Note: All course assignments will use Python as the primary programming language. Java will be used to supplement Python, but learners will not be required to program in Java. **Proficient experience** - Data analysis methods and data reporting conventions. - Mathematical and programming maturity. - Strong Python programming experience. ### Learning outcomes After completing this course, you'll be able to: - Demonstrate familiarity with applications of bio-inspired computing in engineering. - Discuss and use new biological concepts and applications. - Solve computational problems with bio-inspired algorithms. - Use biological concepts and knowledge in algorithms. ### **Estimated workload/time commitment per week** You should expect to spend an average of 18 – 20 hours per week on this course. ### **Technology requirements** **Hardware** - Microphone. - Personal computer. - Reliable, strong internet connection. - Webcam. **Software/other** - PowerPoint or similar presentation software. - Software is supplied within the course. ### **Creator** **Stephanie Forrest** Stephanie Forrest, PhD is a professor of computer science in the School of Computing and Augmented Intelligence (SCAI) at Arizona State University, where she also directs the Biodesign Center for Biocomputation, Security and Society. Prior to joining ASU in 2017, she was a Distinguished Professor at the University of New Mexico where she served as department chair from 2006 to 2011. She is a member of the Santa Fe Institute external faculty, where she has also served as co-chair of its science board and interim VP for academic affairs. From 2013 to 2014, she served in the U.S. Department of State as a senior science advisor for cyber policy. She was educated at St. John's College (BA) and the University of Michigan (MS and Ph.D. in computer science). Forest’s interdisciplinary research focuses on the intersection of biology and computation, including bio-inspired computing, biological modeling and complex systems. In computer science, she focuses on bio-inspired applications in cybersecurity and software engineering. Her research has developed pioneering cybersecurity methods and a new method for automatically repairing software bugs. Her biological modeling work focuses on living systems that consist of large evolving populations, particularly the immune system and several different evolutionary systems. Some of Forest’s awards include the 2020 Test of Time Award from the IEEE Security and Privacy Symposium, the 2019 Ten Year Most Influential Paper Award from the International Conference on Software Engineering, the Santa Fe Institute Stanislaw Ulam Memorial Lectures (2013), the ACM/AAAI Allen Newell Award (2011) and the NSF Presidential Young Investigator Award (1991). She is also a fellow of the IEEE. × ### Foundations of Algorithms ### **About this course** Algorithms, which are step-by-step processes to efficiently reach desired goals, have been a part of human history since the 1200s. Additionally, they are a fundamental component of any computerized system. In this foundational course, you’ll learn several different algorithms and be able to explain how they work and when they’re considered to be good. This knowledge will enable you to: - Develop sound knowledge of algorithms that’ll allow you to navigate the field’s literature beyond the context of this class. - Evaluate appropriate algorithmic techniques that can lead to more efficient solutions for problems instead of just coding the first idea that comes to mind. To gain these skills, you’ll learn how to work through and understand several algorithmic techniques. You’ll also understand the mathematics needed to analyze the properties of these techniques and the algorithms based on them. **Specific topics include:** - Amortized analysis. - Divide-and-conquer. - Dynamic programming. - Greedy algorithms. - Introduction to randomized and approximation algorithms. - Network flows. - NP-completeness. - Stable matching. ### **Required prior knowledge and skills** This course will be very challenging, so learners are expected to possess the needed prior knowledge and skills and/or learn it and necessary technologies on their own time. **Proficient mathematical skills and theoretical understanding** - Asymptotic notation (Big-Oh). - Basic discrete math (e.g., sets, functions, logic and graphs). - Mathematical proofs. - Recurrence relations. - Recursion. - Worst-case analysis. **Strong application skills** Proficiency in programming in at least one of the following programming languages: - C. - C++. - Java. - Python. **Proficient experience** - Data structures and algorithms such as sorting algorithms, hash tables, binary search trees, heaps and red-black trees. - Greedy algorithms, divide-and-conquer and dynamic programming. - Graph algorithms, such as depth-first search, breadth-first search, minimum spanning trees (Kruskal’s and Prim’s algorithms) and shortest-paths (Dijkstra’s algorithm). ### **Learning Outcomes** Upon completing this course, you’ll be able to: - Apply knowledge of algorithms in multiple contexts using programming languages. - Evaluate the correctness and efficiencies of algorithms. - Identify and apply algorithmic techniques to solve problems. ### **Estimated workload/time commitment per week** You should expect to spend an average of 18 – 20 hours per week on this course. ### **Technology Requirements** **Hardware** - Microphone. - Personal computer with a major operating system. - Reliable, strong internet connection. - Webcam. **Software/Other** - Current web browser. - No specialized software or other technology is needed to successfully complete this course. ### **Creator** **Professor Andréa Richa** Andréa Richa, Ph.D. joined Arizona State University in 1998. She’s currently affiliated with the Biomimicry Center and the Biosocial Complexity Initiative in general. Dr. Richa’s main areas of expertise are in distributed/network algorithms and computing. More recently she’s focused on developing the algorithmic foundations on what has been coined as programmable matter through her work on self-organizing particle systems (SOPS). In addition to SOPS, Dr. Richa’s work has been widely cited, including work on bio-inspired distributed algorithms, distributed load balancing, packet routing, wireless network modeling and topology control, wireless jamming, data mule networks, underwater optical networking and distributed hash tables (DHTs). Dr. Richa received the 2017 Best Senior Researcher award from the School of Computing, Informatics and Decision Systems Engineering (CIDSE). She was also the recipient of an NSF CAREER Award in 1999, an associate editor of IEEE transactions on mobile computing and the keynote speaker and program\\general chair of several prestigious conferences. In particular, Dr. Richa was the program committee chair of the 31st International Symposium on Distributed Computing (DISC) in 2017, one of the top two conferences in distributed computing. Dr. Richa has also delivered several invited talks both nationally and internationally. × ### Knowledge Representation and Reasoning ### About this course Knowledge representation and reasoning (KRR) is one of the fundamental areas in artificial intelligence. It is concerned with how knowledge can be represented in formal languages and manipulated in an automated way so computers can make intelligent decisions based on the encoded knowledge. KRR techniques are key drivers of innovation in computer science, and have led to significant advances in practical applications in a wide range of areas from artificial intelligence to software engineering. In recent years, KRR has also derived challenges from new and emerging fields including the semantic web, computational biology and the development of software agents. This is a graduate-level course that introduces fundamental concepts as well as surveys recent research and developments in the field of knowledge representation and reasoning. **Specific topics covered include:** - Classical logic and knowledge representation. - Answer set programming. - Reasoning about actions and planning. - Ontology, semantic web languages and knowledge graph. - Combining logic and probability. **Technologies covered include:** - Answer set programming. - Clingo. ### Required prior knowledge and skills This course will be very challenging, so learners are expected to possess the needed prior knowledge and skills and/or learn it and necessary technologies on their own time. **Proficient mathematical skills and theoretical understanding** - Algebra. - Classical logic. **Strong application skills** - Programming. **Proficient experience** - Ability to effectively read code. - Confidence executing at least one programming language, such as Python, Java, C\#, C++ or C. ### Learning outcomes Learners completing this course will be able to: - Discuss the foundations of KRR. - Explain different categories of representation and reasoning tasks. - Assess the tradeoff between representation and reasoning. - Identify which knowledge-based techniques are appropriate for which tasks. - Apply KRR systems to challenging real-world problems. ### Estimated workload/time commitment per week You should expect to spend an average of 18 – 20 hours per week on this course. ### Technology requirements **Hardware** - Microphone. - Personal computer with a major operating system. - Reliable, strong Internet connection. - Webcam. **Software/other** - Clingo. - Protégé. ### Creator **Joohyung Lee** Joohyung Lee is a tenured associate professor in the School of Computing and Augmented Intelligence at Arizona State University, where he has led the Automated Reasoning Group since 2005. He received his PhD from the University of Texas at Austin. His interests include designing and building intelligent systems, which can perform automated reasoning based on the knowledge represented in a formal language, thereby intelligently handling open-ended tasks by "thinking." He has been working on knowledge representation, logic programming, commonsense reasoning, reasoning under uncertainty, cognitive robotics, computational logics, security and question answering. His research has been supported by the National Science Foundation, Department of Defense, IARPA, Siemens, Bosch and ETRI. He is a recipient of the Outstanding Paper Honorable Mention Award from AAAI 2004. × ### Advanced Computer and Network Security ### About this course Focusing on applied cryptography, system security and the principles and practices of network security, this course explores the necessary tools, techniques and concepts of network security for modern computer networks. The course’s coverage of advanced network security includes both cutting-edge technologies and research topics, primarily at the MAC layer and above. The course not only provides students with exposure to burgeoning areas of network security but also hands-on experience using the tools essential for computer networks and cybersecurity today and in the future. **Specific topics covered include:** - Public key and symmetric key-based cryptography. - Access control models. - Network security policies. - Authentication protocols. - Secure protocol standards. - Public key infrastructure and its development trends. - Virtual private network and its restrictions. - Attack graphs and attack trees. - SDN/NFV-based security solutions. - Cloud network security. - ML and AI for computer network security. - Moving target defense in computer networks. **Technologies covered include:** - Python. - Html. - VirtualBox 5.0. - Apache Web Service. ### Required prior knowledge and skills This course will be very challenging, so learners are expected to learn the necessary technologies on their own time if they do not already possess the necessary skills. **Proficient mathematical skills and theoretical understanding** - Algorithms. - Data structures. - Computer organization and architecture. - Operating systems. - Computer networking. **Strong application skills** - Ability to effectively read C code. - Ability to effectively read Python code. - Confidence executing the following programming languages: - Python. - Java. Note: The course project will be completed using the language the learner chooses; however, the course team will not be able to help the learner if they choose any language that is not Python or Java. **Proficient experience** - Familiarity with these tools to understand network traffic, binaries and web applications for your coursework: - Tcpdump. - Ifconfig. - Route. - Ip. - Ping. - Traceroute. - Basic computer network concepts: - TCP/IP. - Packet switching. - Network services architecture. - Network protocol stack (MAC layer and above). - Basic network security concepts, such as encryption/decryption, authentication, access control and identity/key management. - Basic network security concepts: - Encryption/decryption. - Authentication. - Access control. - Identity/key management. - Operating systems: - Windows 10. - Linux 64 bit. - Mac OS X. ### Learning outcomes Learners completing this course will be able to: - Explain basic security terminologies, models, architectures and techniques. - Apply proven methodologies to design secure networks that address enduring and emerging issues. - Apply network security standards and cryptography algorithms. - Document the process of designing and implementing secure networking systems. - Build a secure networking system to counter given network attacks. - Adhere to standards of computer security ethics. - Manage a network security establishment effort. - Assess networking systems to identify security vulnerabilities. - Represent security system setup and process results in written form. - Discuss cutting-edge network security research and development. ### Estimated workload/time commitment per week You should expect to spend an average of 18 – 20 hours per week on this course. ### Technology requirements **Hardware** - Intel or AMD-based computer with 8GB or more memory. - Note: 6GB is technically sufficient, but performance will be sluggish. - Reliable, strong internet connection. - Webcam. - Microphone. **Software/other** - [VirtualBox 5.0](https://www.virtualbox.org/wiki/Downloads "https://www.virtualbox.org/wiki/Downloads") or newer. - Windows 10, Mac OS X or Linux 64-bit as base operation system. - Knowing how to use the Linux OS is a plus. - Apporto (virtual desktop platform) instead of VirtualBox ### Creator **Dijiang Huang** Dr. Dijiang Huang is an associate professor in the School of Computing and Augmented Intelligence at Arizona State University. He teaches computer network and security at the undergraduate level and advanced computer network and security at the graduate levels. In addition, he taught computer science courses such as computer networks, cloud computing, concepts of computer science and data structure, data structures and algorithms and introduction to computer science and engineering at ASU. Dr. Huang received his Bachelor of Science degree in telecommunications from Beijing University of Posts & Telecommunications, China and his Master of Science in computer science and telecommunications degree and Ph.D. from the University of Missouri-Kansas City. Dr. Huang's research interests are in computer and network security, mobile ad hoc networks, network virtualization and mobile cloud computing. His research is supported by the federal agencies NSF, ONR, ARO and NATO and organizations such as Consortium of Embedded Systems, Kern Family Foundation, Hewlett-Packard and China Mobile. He is a recipient of ONR Young Investigator Award and HP Innovation Research Program award, a Distinguished Lecturer of IEEE ComSoc and a co-founder of Athena Network Solutions LLC and CyNET LLC. He currently leads the Secure Networking and Computing research group at ASU. × ### Applied Cryptography ### About this course Cryptography provides the underlying security methods for the web and many other computer applications. This course covers the design usage of cryptographic protocols for online and offline computing applications. Assuring the quality, validity and privacy of information is one of the key applications of cryptography. Applications of cryptography range from signatures and certificates to trustless multiparty computations. **Specific topics covered include:** - Large numbers, random numbers, hash functions and number theory. - Encryption methods and common ciphers. - Password storage and password cracking. - Authentication, key exchange and man in the middle (MITM) attacks. - Secure messaging, Kerberos and Secure Sockets Layer (SSL) or Transport Level Security (TLS). - RSA and why it works. - Advanced cryptographic protocols. - Anonymity, money and secure election algorithms. **Technologies covered include:** - .NET Core. - C\#. ### Required prior knowledge and skills This course will be very challenging, so learners are expected to possess the needed prior knowledge and skills and/or learn it and necessary technologies on their own time. **Proficient mathematical skills and theoretical understanding** - Discrete math. - Computer organization and architecture. - Operating systems. - Data structures. - Algorithms. - Algebra. - Data Structures. - Computer Organization. - Operating Systems. **Strong application skills** - Linux. - Ability to effectively install and use Linux command line tools. - Ability to effectively read and write. - C\# or confidence in your ability to learn C\# C\# on Linux. - An understanding of C or Java on Linux should be sufficient to get started with C\#. If you do not know C\#, but do know C or Java, there is no reason to avoid taking this course. **Proficient experience** - Clear understanding of what a file is, how it is stored on disk and how to manipulate files. - Experience working with data at the byte level in both data structures and files. - Manipulating bytes of data in variables and in files. - Experience working with numerical data in different radices. - Specifically, base 2, base 10 and base 16. - Representing constants of these bases in code. - Clear understanding of how numbers are represented. - Endianness. - Size restrictions (32-bit Integer, 64-bit Integer, BigInteger). - Experience implementing Algebraic formulas. - Especially logarithms and exponents. - Programming using C or C++ using Linux. - Python or Java is useful. ### Learning outcomes Learners completing this course will be able to: - Differentiate the major algorithmic techniques used in cryptography. - Explain the concept and correctness of cryptographic protocols. - Perform identification of vulnerabilities in systems. - Explain the algorithms used for constructing cryptographic computations. - Perform steps needed for encryption, authentication, integrity, certification and data privacy. - Explain complex protocols that involve many steps and computing agents who do not trust each other. ### Estimated workload/time commitment per week You should expect to spend an average of 18 – 20 hours per week on this course. ### Technology requirements **Hardware** - Standard personal computer with major OS. - Webcam. - Microphone Reliable, strong Internet connection. **Software/other** - Linux Operating System, Ubuntu 18.04 64-bit with administrator capability (ability to install new software). - You can run this OS in a virtual machine, if it is not your main machine. - .NET Core 3.1 SDK. - Hex editor. - You can use an online hex editor. - Access to external websites: C\# documentation, hashing calculator, encryption calculator, etc. ### Creator **Dr. Partha Dasgupta** Partha Dasgupta, PhD is an associate professor in the School of Computing and Augmented Intelligence at Arizona State University. His core areas of expertise are in computer security, cryptography and operating systems. His current research focus is the use of cryptography and secure software systems to provide security and dependability of consumer computing. He has significant prior research results and publications in construction of distributed operating systems, high performance systems and secure computing infrastructures. In addition to ASU, Dr. Dasgupta has held faculty positions at Georgia Tech and New York University. **Dr. Gennaro De Luca** Gennaro De Luca, PhD is a lecturer of information technology with the Polytechnic School in the Ira A. Fulton Schools of Engineering at Arizona State University. He obtained his PhD, MCS and BS in computer science at ASU. He began working at ASU as a full-time lecturer in 2020. His current research interests are in computer science education, workflow programming and artificial intelligence. He has co-authored multiple research papers and textbook chapters on VIPLE, the visual programming language he led development on as part of his undergraduate and doctoral research. × ### Distributed and Multiprocessor Operating Systems ### About this course This course will teach both the fundamental concepts and principles of distributed systems and the practical skills for developing distributed systems. To begin, this course provides an initial exploration of distributed systems and their design goals and types of systems. We address the architectures of distributed systems, including centralized and decentralized architectures and important real-world examples of distributed systems that are built following these architectures. With interprocess communication at the heart of all distributed systems, a concentrated focus will be on a strong series of communication and coordination. To conclude, we take a detailed look at what consistency of replicated data actually means and the various ways that consistency can be achieved. **Specific topics covered include:** - Architecture. - Coordination. - Communication. - Consistency and replication. **Technologies covered include:** - gRPC. ### Required prior knowledge and skills This course will be very challenging, so learners are expected to possess the needed prior knowledge and skills and/or learn it and necessary technologies on their own time. **Proficient mathematical skills and theoretical understanding** - Algebra. - Linear algebra. - Data structures. - Computer organization and architecture. - Operating systems. - Computer networking. **Strong application skills** - Proficiency in programming in at least one of the following programming languages: - Python. - Java. - C\#. - C++. **Proficient experience** - Experience reading technical specifications and documentation. - Experience with virtual machine software: creating, configuration and running virtual machines. ### Estimated workload/time commitment per week You should expect to spend an average of 18 – 20 hours per week on this course. ### Technology requirements **Hardware** - Microphone. - Personal computer with a major operating system and the following: - 8 GB RAM or higher. - An x86-64 CPU. - Ability to install virtual machines on this computer. - Reliable, strong internet connection. - Webcam. **Software/other** - Virtual machine software such as VirtualBox. ### Creator **Ming Zhao** Ming Zhao, PhD is an associate professor at ASU in the School of Computing and Augmented Intelligence. Before joining ASU, he was an associate professor of the School of Computing and Information Sciences at Florida International University. He directs the Research Laboratory for Virtualized Infrastructure, Systems, and Applications. His research is in the areas of experimental computer systems, including cloud/edge, big data/AI and high-performance systems, as well as operating systems and storage in general. Dr. Zhao is a recipient of NSF CAREER award, Air Force Summer Faculty Fellowship, VMware Faculty Award, AWS Machine Learning Research Award and the Best Paper Award of the IEEE International Conference on Autonomic Computing. His research outcomes have been adopted by several production systems. × ### Information Assurance and Security ### About this course The course will provide an overview of the historical underpinnings and the current, global landscape of information assurance and security. Principles and strategies that modern information assurance practices should follow will be highlighted as well as legal and ethical issues. Solidly grasping the theoretical background supports learners to later ethically tackle challenging security tasks. A high-level view of physical and personnel security will be discussed with a focus on authentication and access control. The basics of cryptography, which forms the foundation of modern security, will be addressed, so learners can adopt secure crypto-practices and use secure cryptography in both their daily lives and their development duties. Information assurance in information systems and direct applications of entry-level cryptography in security will be covered. A strong grasp of this content enables learners to recognize common attacks on both local and global networks, and understand the security threats that some seemingly secure practices may entail. The essentials of web security, software security and related emerging problems and vulnerabilities will be featured. Learners taking this course will be challenged to demonstrate concepts and solve problems in a hands-on way in ethical hacking environments. **Specific topics covered include:** - Security and privacy principles. - Physical security. - Personnel security. - Contingency and disaster recovery planning. - Information assurance policies. - Authentication and access control. - Administrative security controls. - Risk analysis and management. - Computer virus and malware. - Network attacking attempts. - Phishing. - Social engineering. - Software security. - Definitions of software security. - Traditional software vulnerabilities. - Modern software vulnerabilities. - Vulnerability discovery. - Vulnerability mitigation. - Secure software development. - Laws and regulations about Information Assurance. - Ethical hacking. **Technologies covered include:** - C. - x86-64 Assembly. - HTTP. - HTML. - JavaScript. - SQL. - Scripting languages. ### Required prior knowledge and skills This course will be very challenging, so learners are expected to possess the needed prior knowledge and skills and/or learn it and necessary technologies on their own time. **Proficient mathematical skills and theoretical understanding** - Algebra. - Linear algebra. - Algorithms. - Data structures. - Computer organization and architecture. - Operating systems. - Computer networking. **Strong application skills** - Ability to effectively read C code. - Ability to effectively read Python code. - Confidence executing at least one programming language: - Python. - Java. - C\#. - C++. - C. Note: The course project will be completed using the language that the learner chooses. However, the course team will not be able to help the learner if they choose any language that is not Python, Java or C\#. **Proficient experience** - Clear understanding of theoretical and applied industry-relevant operating systems and computer networks. - Example: Ethernet, ARP, Routing, IP Addresses, Fragmentation, ICMP, UDP, TCP and x86-64 assembly. - Experience reading technical specifications and documentation. ### Learning outcomes Learners completing this course will be able to: - Recognize common security threats and attacking attempts. - Identify typical vulnerabilities in programs. - Develop secure programs. - Analyze legal and ethical concerns of computer security activities. - Launch attacks in ethical hacking environments. ### Estimated workload/time commitment per week You should expect to spend an average of 18 – 20 hours per week on this course. ### Technology requirements **Hardware** - Personal computer with a major operating system and 8 GB RAM or higher and an x86-64 CPU. - Must be able to install virtual machines on this computer. - Computers with ARM processors (or any other architecture) will not work. - Reliable, strong Internet connection with unrestricted access to key websites that are commonly used in software development activities. - Example: GitHub and Stack Overflow. - Webcam. - Microphone. **Software/other** - Linux (Ubuntu 20.04 is recommended) ([Ubuntu 20.04 LTS](https://releases.ubuntu.com/20.04/)). - A virtual machine application, such as VMware, is recommended for non-Linux users. - You can get [VMware](https://ets.engineering.asu.edu/vmware/) for free as an ASU learner (strongly recommended) and install Ubuntu 20.04 in a VM. Most reference codes will be provided as a Python script. Therefore, Python is strongly recommended. - Note: For some coursework, the course team will not be able to help you if you choose any language that is not Python, Java, or C\#. Therefore, to create the best learning experience, Python is strongly recommended. This is noted on the overview docs where it applies. - Browser (e.g., Chrome, FireFox, or Microsoft Edge), an HTTP request sender (curl), and Burp Suite. - Ability to access AWS resources. - You are strongly encouraged to use Python 3 and the [scapy package](https://scapy.net/). ### Creator **Ruoyu Wang** Ruoyu (Fish) Wang, PhD is an assistant professor in the School of Computing and Augmented Intelligence at Arizona State University. He conducts research on system security, with focus on automated binary program analysis and reverse engineering of software. He's the co-founder and core developer of the binary analysis platform, angr. He won third place with team Shellphish in the DARPA Cyber Grand Challenge in 2018. × ### Mobile Computing ### About this course The goal of this course is to provide an in-depth understanding of the fundamental concepts and challenges in mobile computing, as well as and study the existing and proposed solutions for these challenges from research and development perspectives. Topics covered in this course include mobile app development, wireless communication, mobile technology management, mobility tracking, context awareness and programming applications on mobile systems. Coursework will involve programming assignments, discussions, quizzes and a project. **Specific topics covered include:** - Mobile programming. - Internet of Things (IoT). - Edge and cloud computing. - Mobile networking. - Mobile information access. - Adaptive applications enabled by machine learning and AI. - Energy-aware systems. - Location-aware computing. - Mobile security and privacy. **Technologies covered include:** - Android Application Development. - Java. - Python. - Tensorflow. ### Required prior knowledge and skills This course will be very challenging, so learners are expected to possess the needed prior knowledge and skills and/or learn it and the necessary technologies on their own time. **Proficient mathematical skills and theoretical understanding** - Networking. - Operating systems. - Security. - Probability. - Statistics. - Algorithms. **Strong application skills** - Ability to read Python code. - Ability to write Java and Python code. Note: The course projects will be completed using the Android application development environment and Python. **Proficient experience** - Understanding of mobile computing system models. - Mobile networking: Mobile device routing, Handoff, ARP. - Experience reading research papers. - Understanding of context-aware applications and the role of device usage, mobility patterns in context-aware applications. - Mobile application security. - Understanding energy and power consumption of a mobile application. ### Learning outcomes Learners completing this course will be able to: - Design a context-aware application. - Identify the advantages of using context in applications. - Explore the challenges arising due to changes in the environment in which computation is performed. - Identify relevant environment changes and analyze their causes, such as mobility, availability of data, and resource constraints. - Define smartness and identify salient features that distinguish smart applications from traditional ones in the context of smart city, smart grid, smart transportation, smart mobile applications, and autonomous systems, such as autonomous cars. - Describe key features of the Internet of Things (IoT) and design a distributed smart application using IoT. - Define cloud computing, crowdsourcing, volunteer computing and other novel variants of pervasive computing. - Analyze nonfunctional requirements of smart mobile applications, such as safety, security and sustainability. - Apply popular tools, such as machine learning, security protocols, AI and software testing, to validate safety security and sustainability of smart mobile applications. - Acquire programming skills on popular mobile platforms, such as Android. - Develop, end-to-end, a sensor-enabled smart autonomous practical application. ### Estimated workload/time commitment per week You should expect to spend an average of 18 – 20 hours per week on this course. ### Technology requirements **Hardware** - Microphone. - Personal computer with the following: - At least 2GB RAM (4GB RAM recommended). - At least 1GHz (2GHz or more recommended) - Windows 7 or higher / OS X v10.7 or higher. - Reliable, strong internet connection. - Webcam. **Software/other** - Android Studio Integrated Development Environment (IDE) with the software development kit (SDK) bundle (check the system required for Android Studio on their website). - Gradescope (for submission). - Python3 (recommended 3.10). - Pandas 2.1.4. - Numpy 1.26.3. - Scikit-learn 1.3.2. - OpenCv 4.9.0.80. - Tensorflow 2.15.0. - Flask for your local server. - YouTube account. - GitHub account. ### Creator **Dr. Ayan Banerjee** Dr. Banerjee is an assistant research professor in the School of Computing and Augmented Intelligence at Arizona State University. His research interests include pervasive computing in healthcare and analysis and safety verification of embedded system software. Dr. Banerjee currently focuses on data-driven analysis and modeling in many different domains including diet monitoring, gesture recognition and biological process modeling. He works closely with government agencies, such as the Food and Drug Administration, and medical agencies, such as Mayo Clinic. Dr. Banerjee is also interested in hybrid system-based modeling and safety verification of closed-loop control systems that interact with the physical environment, also known as Cyber-Physical Systems. In addition, his work includes developing management algorithms for sustainable data centers using renewable sources of energy.

Offered through Arizona State University’s School of Computing and Augmented Intelligence, the online Master of Computer Science (MCS) is designed for those interested in expanding their knowledge of computer science and computation. In this program, you’ll gain an advanced understanding of topics such as artificial intelligence, cybersecurity and big data, while strengthening your skills through technical projects. [Learn more](https://asuonline.asu.edu/online-degree-programs/graduate/computer-science-mcs/#program-detail) Quick facts  Next start date: 05/18/2026 ***  Total classes: 10  Weeks per class: 7\.5  Total credit hours: 30 ## Prepare for in-demand high-paying jobs with a computer science master’s Organizations across industries from health care and business to engineering and education rely on those with computer science knowledge and skills. According to the U.S. Bureau of Labor Statistics, employment for computer and information research scientists is expected to grow by 23% from 2022 to 2032, which is much faster than average for all occupations. Earning a Master of Computer Science is a step toward advancing your career in a lucrative field. Computer and information research scientists made a median annual salary of \$136,620 in May 2022, according to the U.S. Bureau of Labor Statistics. ## The skills you’ll develop in this master’s program This Master of Computer Science program is designed to build your knowledge about a range of topics from designing software for networks, graphics and database systems to integrating computer science with biology, geography, public health and more. Upon graduation, you’ll have a variety of skills, including: - Designing and analyzing computers. - Implementing computational processes. - Improving software reliability, network security and information retrieval systems. - Inventing next-generation computer systems, computer networking, biomedical information systems, gaming systems and more. - Transferring and transforming information.  ### Professional certification and nondegree enrollment opportunities 1. As a nondegree-seeking graduate student, you can take master’s-level computer science courses without being admitted to the program. This provides you the opportunity to establish a high graduate GPA, try out courses, meet the English proficiency requirement or earn a professional certification credential. Those who complete three courses with a cumulative GPA of at least 3.00 after the first attempt can use this GPA and the credit hours earned when applying for the Master of Computer Science program. You must also meet all prerequisite requirements to be admitted. [Learn more](https://goto.asuonline.asu.edu/mcs-professional-certifications/)  ### Will my diploma say ‘online’? No, Arizona State University’s diplomas don’t specify whether you earn your degree online or in person. All diplomas and transcripts simply say “Arizona State University.” ## Computer science master’s courses You’ll choose one course in each of three primary areas of study: theoretical foundations, systems and applications. You’ll also take several elective courses on topics ranging from statistical machine learning and mobile computing to data mining and information assurance. Foundations ### Bio-Inspired Computing *** Foundations ### Foundations of Algorithms *** Foundations ### Knowledge Representation and Reasoning *** Systems ### Advanced Computer and Network Security *** Systems ### Applied Cryptography *** Systems ### Distributed and Multiprocessor Operating Systems *** Systems ### Information Assurance and Security *** Systems ### Mobile Computing *** The roles a master’s in computer science prepares you for This program can give you a leg up and advance your career in a variety of technical disciplines. Upon graduating, you’ll be equipped to pursue career paths ranging from software engineering, cloud computing and machine learning information security to application development, software QA and web development. Roles you may pursue include, but aren’t limited to: Computer network analyst Computer programmer Computer scientist Computer systems analyst Database administrator Information technology manager SEO specialist Software developer  ### Study with award winning faculty members in the field of computer science Of the 350+ faculty members in Ira A. Fulton Schools of Engineering, the majority have been honored with the highest awards in their fields. Faculty milestones include: - National Academy of Engineering members. - National Academy of Sciences member. - National Academy of Inventors members. - National Academy of Construction members.  ### Study with award winning faculty members in the field of computer science Of the 350+ faculty members in Ira A. Fulton Schools of Engineering, the majority have been honored with the highest awards in their fields. Faculty milestones include: - National Academy of Engineering members. - National Academy of Sciences member. - National Academy of Inventors members. - National Academy of Construction members. How to apply This program has a highly competitive admission process. Top 25% of all accredited engineering programs in the nation The Ira A. Fulton Schools of Engineering is dedicated to providing a dynamic learning environment and supporting all students on the paths to their degrees. We’ve received numerous peer-reviewed programmatic honors from U.S. News & World Report. ### \#2 *** best online master’s in electrical engineering programs. ### \#2 *** best online master’s in engineering management programs. ### Top 5 *** for bachelor’s degrees awarded to underrepresented minorities (American Society for Engineering Education 2022). ### Top 10 *** best online master’s in engineering programs for veterans.  ### Tuition calculator Use our calculator to estimate your full-time or part-time tuition fees for this program prior to any financial aid. Keep in mind that most of our students receive financial aid, which can reduce out-of-pocket costs. [Learn more.](https://asuonline.asu.edu/what-it-costs/financial-aid/)  ### Tuition calculator Use our calculator to estimate your full-time or part-time tuition fees for this program prior to any financial aid. Keep in mind that most of our students receive financial aid, which can reduce out-of-pocket costs. [Learn more.](https://asuonline.asu.edu/what-it-costs/financial-aid/) View the most commonly asked questions You might also be interested in  Graduate Computer Science – Cybersecurity (MCS)  Graduate Graphic Information Technology (MS)  Graduate Information Technology (MS)  Graduate Computer Science – Big Data Systems (MCS)