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.

ÌýÌýImportant Update: Machine Learning Specialization ChangesÌýÌýÌý

We are excited to inform you the current Machine Learning: Theory and Hands-On Practice with Python Specialization (taught by Professor Geena Kim) is being retired and will be replaced with a new and improved version (to be taught by Professor Daniel Acuna) that reflects the latest advancements in the field. The last opportunity to sign up for the current version will be July 1, 2025. The new version will be available starting Fall 1, 2025.

  • You will have access until December 1, 2025.
  • After this date, you will be able to enroll in the new specialization.Ìý

No. Since the old non-credit Machine Learning specialization was phased out, for whichever course(s) you did not complete in the new specialization, you will need to complete them in the new non-credit specialization in order to receive the Coursera Completion Certificate.Ìý

A Coursera completion certificate is an official credential issued by Coursera and its partner universities, verifying that a learner successfully completed a specialization and demonstrated a comprehensive understanding of the course material. This is not to be confused with earning academic credit from CU Boulder.Ìý

The content is updated to reflect the current curriculum and advances in the field.ÌýÌý

All courses in this specialization are graduate level courses and students are expected to come to the courses with the necessary prior knowledge. We encourage you to preview the courses in the non-credit version first.Ìý

Yes. However, there will be fewer than in the previous version.Ìý

If you are interested in earning the completion certificate and feel comfortable with completing Geena’s full specialization before the enrollment deadline, feel free to enroll. You will have until December 1 to complete the material in order to receive the completion certificate.Ìý

You have a few options:

  • You can enroll in Professor Kim's full specialization now if you feel comfortable with the session deadlines.
  • You can enroll in part of Professor Kim's specialization now and do the remainder of the specialization in Professor Acuna's specialization after fall 1.
  • You can wait to complete the new specialization (Professor Acuna) starting in fall 1.
  • Remember that If you are interested in earning a completion certificate from Coursera, you need to complete either Professor Kim’s version in full, or Professor Acuna’s version in full.Ìý
  • Yes, any progress you have completed will not carry over to the new specialization. We recommend saving work off-platform.
  • If you have already earned academic CU Boulder credit for any Machine Learning courses, you will not need to re-do these courses in the new specialization.Ìý

Yes, the new version will count toward the Machine Learning requirement in the MS-CS degree, the MS-DS degree, The MS-AI degree, the DS graduate certificate and the AI graduate certificate. Even if you mix and match the courses in the specialization between the old and new versions.ÌýÌý

No. The new version of the specialization is the updated version of the same specialization with the same course codes.Ìý

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Degree requirements apply to the academic year that you enrolled in at least one course for-credit, not your admission year. Check your Degree Audit in your to verify your degree progress and requirements.Ìý

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Any new or existing CSCA electives will count toward all catalog year degree requirements. The exceptions being the Foundations of Autonomous Systems (2024-25 catalog Breadth requirement) and Software Architecture for Big Data (2023-24 catalog Breadth requirement). See Electives section below.Ìý

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 their 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 University of Colorado Boulder 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 Boulder'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 Boulder 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)

ÌýÌýImportant Update: Machine Learning Specialization ChangesÌýÌý

We are excited to inform you the current Machine Learning: Theory and Hands-On Practice with Python Specialization (taught by Professor Geena Kim) is being retired and will be replaced with a new and improved version (to be taught by Professor Daniel Acuna) that reflects the latest advancements in the field. The last opportunity to sign up for the current version will be July 1, 2025. The new version will be available starting Fall 1, 2025.

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 Boulder 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.
  • NOTE: Any new or existing CSCA electives will count toward all catalog year degree requirements. The exceptions being the Foundations of Autonomous Systems (2024-2025 catalog Breadth requirement) and Software Architecture for Big Data (2023-2024 catalog Breadth requirement). Ìý
  • As new CSCA electives are released, they will still apply to your MS-CS degree if you would like to take them. Because the degree was launched in Fall 2023 we were not able to capture all electives that were not released yet on the degree audit for students in the 2023-2024 catalog year, so you may not see them on your degree audit.ÌýWhen you see new CS electives on your degree audit, they may pull into the "Computer Science Undefined Specialization" on your degree audit, and they still count toward electives.

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.

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

Security and Ethical HackingÌý(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.

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

  • CSCA 5403: Introduction to Cybersecurity
  • CSCA 5413: Data Security and Software Security
  • 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.

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

  • CSCA 5113: Users, Permissions and Command Line Use
  • 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.

*Admitted students will receive an email regarding Outside Electives at the end of every session after grades post. This email has the form to give the program permission to apply your outside electives to your degree. Students must earn a C grade or better to apply outside electives.
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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 Boulder Graduate Certificates on Coursera

You can also pursue graduate CU certificates on Coursera on the way to your MS-AI 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-AI on Coursera Student HandbookÌýoutlines those steps and other important considerations, including rules preventing students from double counting courses between multiple certificates.​