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| Meta Title | Upper-Division CS Course Descriptions | School of Computing - College of Engineering | USU |
| Meta Description | Course descriptions for elective and upper-division courses in the computer science department. |
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| Boilerpipe Text | In response to the rapid integration of AI across industries, the Computer Science Department has embedded AI principles, tools, and applications into the following elective courses: CS 4320, CS 4460, CS 4610, CS 5000, CS 5030/6030, CS 5040/6040, CS 5080, CS 5110/6110, CS 5215/6215, CS 5270/6270, CS 5330/6330, CS 5600/6600, CS 5615/6615, CS 5620/6620, CS 5640/6640, CS 5665, CS 5680/6680, CS 5710, CS 5715/6715, CS 5840/6840, and CS 6460.
CS majors must be accepted to the professional program before registering for upper-division CS coursework. Students may request an exception to this rule via the
Upper-Division CS Course Request Form
.
All the courses are 3 credits except for a few courses listed otherwise.
A grade of C- or better is required in all prerequisite courses. |
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# Upper-Division CS Course Descriptions
Recommended Electives for Careers
CS 3XXX/4XXX Courses
CS 5XXX/6XXX Courses
Computer Science Career Resources
**Warning\!** This page is currently being updated for the 2025-2026 academic year. Please check back later for completely up-to-date information.
In response to the rapid integration of AI across industries, the Computer Science Department has embedded AI principles, tools, and applications into the following elective courses: CS 4320, CS 4460, CS 4610, CS 5000, CS 5030/6030, CS 5040/6040, CS 5080, CS 5110/6110, CS 5215/6215, CS 5270/6270, CS 5330/6330, CS 5600/6600, CS 5615/6615, CS 5620/6620, CS 5640/6640, CS 5665, CS 5680/6680, CS 5710, CS 5715/6715, CS 5840/6840, and CS 6460.
CS majors must be accepted to the professional program before registering for upper-division CS coursework. Students may request an exception to this rule via the [Upper-Division CS Course Request Form](https://engineering.usu.edu/cs/students/undergraduate/pre-professional-program.php).
All the courses are 3 credits except for a few courses listed otherwise.
A grade of C- or better is required in all prerequisite courses.
## CS 3XXX/4XXX Courses
## CS 5XXX/6XXX Courses
All CS 5XXX courses have only CS 2420 as a course prerequisite, except for a few courses listed otherwise.
CS 6XXX courses are restricted to graduate students in the CS department. Undergraduate CS students and graduate students outside of CS may register provided prerequisites for the dual-listed CS 5XXX course is met, or instructor permission is provided.
A grade of C- or better is required in all prerequisite courses.
## Recommended Electives for Careers
Artificial Intelligence/Machine Learning Developer:
- CS 3430 β Scientific Computing
- CS 4320 β Applied Machine Learning
- CS 5110 β MultiAgent Systems
- CS 5600 β Intelligent Systems
- CS 5615 β Natural Language Processing
- CS 5640 β Artificial Neural Networks
- CS 5665 β Machine Learning for Data Science
- CS 5680 β Computer Vision: Foundations & Applications
Security Analyst:
- CS 3460 β Modern C++
- CS 4460 β Introduction to Cybersecurity
- CS 5215 β Computer Networks and Security
- CS 5710 β Software Security
- CS 5715 β Program Analysis and Its Application
- CS 6460 β Usable Privacy and Security
Software Developer/Engineer:
- CS 4460 β Introduction to Cybersecurity
- CS 4610 β Modern Web Development
- CS 5050 β Advanced Algorithms
- CS 5300 β Compiler Construction
- CS 5330 β Data-Driven Programming Language Processing
- CS 5470 β Introduction to Interactive Virtual Reality
- CS 5700 β Object-Oriented Software Development
- CS 5800 β Introduction to Database Systems
Cloud Developer:
- CS 4610 β Modern Web Development
- CS 5030 β High Performance Computing
- CS 5270 β Introduction to Cloud Development
Data Science Analyst:
- CS 4320 β Applied Machine Learning
- CS 5040 β Scientific Visualization for Data Science or CS 5820 β Interactive Information Visualization for Data Science
- CS 5080 β Introduction to Data Mining
- CS 5840 β Graph Mining
- CS 5850 β Introduction to Data Analysis
- CS 5665 β Machine Learning for Data Science
- CS 5830 β Data Science in Practice
Mobile Application Developer and Web Developer:
- CS 4460 β Introduction to Cybersecurity
- CS 4610 β Modern Web Development
- CS 5140 β Human Factors in Computing
- CS 5800 β Introduction to Database Systems
Game Developer:
- CS 3460 β Modern C++
- CS 5050 β Advanced Algorithms
- CS 5300 β Compiler Construction
- CS 5400 β Computer Graphics I (taught infrequently)
- CS 5410 β Game Development
Startup Entrepreneurs:
- CS 5311 β Technology Startup Business Principles
- CS 5312 β Modern Technology Stacks
- CS 5313 β Technology Startup Software Engineering
- CS 5314 βTechnology Startup Business Launch
- CS 5315 β Computer Science Innovations
- CS 5316 β Commercial Software Engineering
[Computer Science](https://engineering.usu.edu/cs/index.php)
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| Readable Markdown | In response to the rapid integration of AI across industries, the Computer Science Department has embedded AI principles, tools, and applications into the following elective courses: CS 4320, CS 4460, CS 4610, CS 5000, CS 5030/6030, CS 5040/6040, CS 5080, CS 5110/6110, CS 5215/6215, CS 5270/6270, CS 5330/6330, CS 5600/6600, CS 5615/6615, CS 5620/6620, CS 5640/6640, CS 5665, CS 5680/6680, CS 5710, CS 5715/6715, CS 5840/6840, and CS 6460.
CS majors must be accepted to the professional program before registering for upper-division CS coursework. Students may request an exception to this rule via the [Upper-Division CS Course Request Form](https://engineering.usu.edu/cs/students/undergraduate/pre-professional-program.php).
All the courses are 3 credits except for a few courses listed otherwise.
A grade of C- or better is required in all prerequisite courses. |
| Shard | 171 (laksa) |
| Root Hash | 2091960294454258171 |
| Unparsed URL | edu,usu!engineering,/cs/students/resources/course-descriptions s443 |