Curriculum & Degree Requirements

The MS-CS requires a minimum of 30 credit hours of approved, degree-eligible graduate-level coursework. Before graduation, students must have a minimum cumulative grade-point average (GPA) of 3.00 and a grade of B or better in each breadth class (including the two required pathways).

To avoid confusion, we will not provide estimated course release dates. Confirmed release dates will be posted next to course titles when available.

Degree Requirements apply to the academic year that you enrolled in at least one course for-credit, not your admission year.

Students that enrolled in at least one course for-credit in the 2023-2024 Academic Year (Fall 1, 2023 - through Summer 2, 2024) follow the 2023-2023 Catalog:

Check your Degree Audit in your Buff Portal to verify your degree progress and requirements:

2024-2025 MS-CS Degree Requirements and Curriculum

Prerequisites Degree Requirements Performance-Based Admissions Curriculum Overview Pathway Specializations Breadth Electives Outside Electives
Prerequisites

This program does not require formal prerequisites, we recommend learners be familiar with particular subjects. See Are there any prerequisites to for the program?Ìýon our FAQÌýpage for an outline of those subjects and suggested basic courses. These suggested courses are not required and do not count for credit toward the MS-CS degree. Click on course titles to review the course syllabus, including prior knowledge needed for each course.

What to Expect:

  • This is a graduate level program and students should have equivalent prior knowledge of college level coursework and comport themselves as a graduate professional with their peers, program staff and faculty and all communication channels.
  • Students should be comfortable in a self-motivated learner environment.
  • Students are expected to read and understand program policies, follow course instructions and read carefully, and reach out through proper channels for support.

This degree is designed for students who have:

  • A strong foundation in computer science either via education or professional experience.
  • Programming and software development experience.
  • A college level understanding of calculus, linear algebra, discrete math, probability and statistics.

The MS-CS on Coursera is a non-thesis degree program that requires 30 credit hours of graduate-level coursework. This includes 15 credits of required Breadth courses, including the Pathway courses, and a choice of 15 Elective credits. Students must either complete 5 Elective specializations or a combination of 4 complete Elective specializations and three 1-credit Electives totaling 15 credits.

Each course is one credit and most courses are arranged in 3-course specializations. These specializations cover the same content that a 3-credit, 16-week course would cover. Please see the for further details. Current students can verify thier degree requirements and degree progress in their degree audit in the .

Keep in mind:

  • You may complete courses in any order.
  • You do not need to wait to be admitted to take more courses and make progress on your degree.
  • When you complete all three courses in one pathway with a B or better in each course, you are automatically admitted after the session you completed the Pathway courses.
  • Credits you earn before admission will apply toward the degree.
  • You must earn a B or better in your Breadth courses, and C or better in your Electives courses for credit toward your degree.
  • Courses with grades below these minimums will not count toward your degree, but they will apply to your GPA.
  • Students are required to maintain a minimum cumulative GPA of 3.00.
  • Students may retake any course they want, but you can only repeat the same course once.
  • This program qualifies for grade replacement.
  • Courses may not be double-counted toward two credentials of the same level. This means students can apply credit from a particular course toward one graduate certificate and one graduate degree, but they cannot apply credit from a one course toward two graduate certificates or two graduate degrees.

The MS-CS on Coursera uses performance-based admissions, which means students earn program admission simply by performing well in a three-course Pathway specialization. To be admitted to the program, students enroll in and complete their preferred three-course Pathway specialization with a grade of B or better in each of the three courses, have a cumulative GPA of at least 3.00 for all for-credit courses taken to date, and declare intent to seek the degree via the enrollment form. Pathway courses are a required part of the curriculum, which means students make direct progress toward the degree while they work toward program admission.

There is no traditional application for admission to the degree. The Â鶹ӰԺ never asks for transcripts, previous test scores (like GRE or TOEFL), application essays, letters of recommendation, or application fees. A prior degree is not required for admission. Because this program is fully online, students do not need to complete a background check to enroll.

The Master of Science in Computer Science (MS-CS) program hosted online through the Coursera platform offers stackable graduate-level courses, a graduate certificate, and a fully accredited master’s degree in computer science. MS-CS on Coursera students earn the same credentials as on-campus students. There are no online or Coursera designations on official CU transcripts or diplomas.

The Department of Computer Science has embraced this degree as an ideal opportunity to expand access to the excellent graduate-level courses offered by the department's highly reputed faculty beyond CU Â鶹ӰԺ's physical campus. The goal of the MS-CS on Coursera program is to produce creative, workforce-ready graduates equipped with versatile specialized skills and technical leadership.

Students pursuing this degree will also have access to a wide range of courses taught as part of other CU Â鶹ӰԺ degrees offered on the Coursera platform, including topics such as data science, engineering management, and electrical engineering

We highly recommend that students start all of their courses in the non-credit, open, version in Coursera. When you work on the course in the public (not-for-credit) version, you can work at your own pace and redo assignments. Then, when you are ready to enroll for credit, you use the enrollment form, pay tuition and complete onbaording, the progress you made on the coursework in the public version will transfer into the for-credit version. Then, you will access the restricted for-credit content (usually a final exam or project) and complete the requirements by the session deadlines for credit.

Read more about the Curriculum and Courses in the next sections.

Complete ONE Pathway specialization with a B or better in each course for admission.

Complete BOTH pathways for the degree. Both of the Pathway specializations are part of the Breadth requirement for the degree.

Pathway | Breadth: Foundations of Data Structures and Algorithms (3 credits)

Pathway | Breadth: Network Systems: Principles and Practice (Linux and Cloud Networking) (3 credits)

There are 15 required Breadth courses, including the Pathway Breadth courses. Once you complete a Pathway Breadth specialization with a B or better in each course, you are admitted to the program.

Pathway | Breadth: Foundations of Data Structures and Algorithms (3 credits)

Pathway | Breadth: Network Systems: Principles and Practice (Linux and Cloud Networking) (3 credits)

Breadth:

Machine Learning: Theory & Hands-On Practice with PythonÌý(3 credits)

Computing, Ethics, and Society (3 credits)

Foundations of Autonomous SystemsÌý(3 credits)

Select 15 Elective credits, including at least four full specializations.Ìý

  • You may choose to complete five specializations or a combination of four specializations plus three 1-credit courses from different specializations.
  • Up to six credits/2 specializations from other CU Â鶹ӰԺ degrees on Coursera can be applied toward MS-CS elective credit requirements. See Outside ElectivesÌýbelow for details.
  • To avoid any confusion we will not provide estimated release timelines of courses/specializations that are in development.

Software Architecture for Big Data (3 credits)

Data Mining Foundations and Practice (3 credits)

Introduction to Robotics with Webots (3Ìýcredits)

Object-Oriented Analysis & Design (3 credits)
This specialization is currently in development.

Generative AI (3 credits)
This specialization is currently in development.

Internet Policy: Principles and Problems (3 credits)
This specialization is currently in development.

Introduction to Computer Vision (3 credits)
This specialization is currently in development.

Security and Ethical HackingÌý(3 credits)
This specialization is currently in development.

Introduction to CybersecurityÌý(3 credits)
This specialization is currently in development.

  • CSCA 5403: Introduction to CybersecurityÌý
  • CSCA 5413: Data Security and Software SecurityÌý
  • CSCA 5423: Human, Organizational, and Societal SecurityÌý

Introduction to Human-Computer InteractionÌý(3 credits)
This specialization is currently in development.

  • CSCA 5859: Ideating and Prototyping Interfaces
  • CSCA 5869: User Interface Testing and Usability
  • CSCA 5879: Emerging Topics in HCI: Designing for VR, AR, AI

Big Data Challenges and NoSQL SolutionsÌý(3 credits)
This specialization is currently in development.

Natural Language Processing: Deep Learning Meets Linguistics (3Ìýcredits)
This specialization is currently in development.

  • CSCA 5832: Fundamentals of Natural Language Processing
  • CSCA 5842: Deep Learning for Natural Language Processing
  • CSCA 5852: Model and Error Analysis for Natural Language Processing

Linux System Administration (3Ìýcredits)
This specialization is currently in development.

  • CSCA 5113: Users, Permissions and Command Line UseÌý
  • CSCA 5123: Installing and Maintaining Software and Hardware
  • CSCA 5133: Networking and Security

Standalone Elective Courses

These one-credit courses are not part of any specialization. Remember you must complete four full specializations to earn the MS-CS. These courses are currently in development.

You can apply up to six graduate-level credit hours/2 specializations of courses offered by other CU degrees on Coursera toward the MS-CS on Coursera degree*. All courses must be graduate level, offered through Coursera, and meet all applicable academic standards. This includes all courses offered by the ME-EM on Coursera, the MS-DS on Coursera, and the MS-EE on Coursera programs except the following courses.

*If you are applying outside elective credits to your degree, please contact the MS-CS program advisor at mscs-coursera@colorado.edu after your grade posts for the courses.
Ìý
You cannot apply credit from the following courses toward MS-CS on Coursera 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 - The exclusion of this course will take effect in AY 24-25. If you took this course for credit in AY 23-24 this course was still part of your catalog year and accepted toward electives in the MS-CS degree.

Courses that begin with a "CSCA" prefix and courses that are cross-listed with a CSCA-prefixed course are not considered outside electives and do not count against this six-credit limit. Ìý

If you wantÌýto complete degrees in more than one program, you must complete all the requirements for both degrees with no shared or overlapping course work.

CU Â鶹ӰԺ Graduate Certificates on Coursera

You can also pursue graduate CU certificates on Coursera on the way to your MS-CS degree. Currently, the following programs offer graduate CU certificates on Coursera:

CU certificates on Coursera are stackable.ÌýThat means you can count credits first earned as part of a CU certificate toward the 30-credit MS-CS degree. To earn a CU certificate on Coursera, you must maintain a cumulative certificate GPA of 3.00 or higher. Individual certificates may have additional requirements. CU certificates on Coursera are automatically awarded once all requirements are met.Ìý

Make sure you take courses in the correct order and complete all steps to earn the certificates you are most interested in.ÌýAdditional steps are required to earn certificates offered by other CU degrees on Coursera. TheÌýMS-CS on Coursera Student HandbookÌýoutlines those steps and other important considerations, including rules preventing students from double counting courses between multiple certificates.​