Master of Science in Computer Science

Yes. Learners can begin in the non-credit version of the coursework, explore the curriculum before committing to the degree, and later upgrade to the for-credit version during an open enrollment period. See how it works.

The program is delivered 100% online through lecture videos, hands-on projects, and interaction with instructors and peers. It is self-paced, with no required minimum number of courses per session. New students are encouraged to start with one course, and many students move to about three courses per session after their first term. At that pace, the degree can be completed in about two years. Students must complete the full 30 credit hours within eight years.

When you successfully complete the online MS-CS degree, you may come to campus to participate in the graduation ceremony.

The online and on-campus versions are overseen by the same faculty. Students also have access to weekly office hours led by dedicated course facilitators, along with online university resources such as libraries, career services, and alumni services.

Total tuition is $15,750, based on $525 per credit hour for 30 credit hours. Students pay only for the courses they take in the upcoming session, which makes it possible to spread tuition over time and take a session off without penalties. The listed price includes course access, exam proctoring, dedicated support, and career resources.

The program accepts up to six graduate-level credit hours from eligible CU degree programs on Coursera as elective credit, subject to academic rules. This includes all courses offered by the ME-EM, MS-DS, and MS-EE programs on Coursera that do not start with a "CSCA" prefix, with the exception of the following courses.

Credit from these courses cannot be applied toward MS-CS requirements:

• DTSA 5302 Cybersecurity for Data Science
• DTSA 5303 Ethical Issues in Data Science
• DTSA 5501 Algorithms for Searching, Sorting, and Indexing
• DTSA 5502 Trees and Graphs: Basics
• DTSA 5707 Deep Learning Applications for Computer Vision

It does not accept transfer credit from other institutions.

The program is open to students around the world except in countries or regions where U.S. sanctions restrict online course delivery. English-language tests are not required for admission because entry is based on performance in the pathway courses rather than a traditional application process.

A cross-listed course is offered under two or more CU Boulder degree programs on Coursera. For example, Dynamic Programming, Greedy Algorithms is offered as both CSCA 5414 for the MS-CS and DTSA 5503 for the MS-DS.

• You may not earn credit for more than one version of a cross-listed course.
• You can identify cross-listed courses by checking your program’s student handbook.
• Your transcript will be affected. Cross-listed courses are considered equivalent when evaluating graduation requirements. However, we encourage you to take your program's versions of cross-listed courses (when available) to ensure your CU transcript reflects the substantial amount of coursework you are completing directly in your home department. Any courses you complete from another program will appear on your CU transcript with that program’s course prefix (e.g., DTSA vs. CSCA).
• Programs may have different minimum grade requirements for admission and graduation. For example, the MS-DS requires a C or better on all courses for graduation (and a 3.0 pathway GPA for admission), whereas the MS-CS requires a B or better on all breadth courses and a C or better on all elective courses for graduation (and a B or better on each pathway course for admission). All programs require students to maintain a 3.0 cumulative GPA for admission and graduation.

An outside elective (sometimes called an “external” elective) is a course offered by another CU Boulder degree program on Coursera. You may apply credits earned from outside elective courses to complete your degree’s elective requirements. Tuition rates vary by program. Credit limits apply and not all courses are applicable to all degree programs. See your program’s student handbook for details and restrictions.

The following courses are not considered outside electives:

• Courses offered by your degree program: You can identify courses offered by your degree program by the four-letter prefix before the course number: Computer Science: CSCA, Data Science: DTSA, Electrical Engineering: ECEA, Engineering Management: EMEA
• Courses that are cross-listed with a course offered by your degree program: You can identify cross-listed courses by checking your program’s student handbook.

For example, Data Mining Pipeline is a one-credit cross-listed course available as both DTSA 5504 and CSCA 5502. CSCA 5502 is not considered an outside elective for Data Science students, and DTSA 5504 is not considered an outside elective for Computer Science students. These courses would be considered outside electives for Electrical Engineering and Engineering Management students because they are not cross listed with ECEA or EMEA courses, respectively.