FAQ

General Program Information

The MS-CS on Coursera falls under the 񱦵’s overall accreditation by the . This accreditation is recognized by the and the . The HLC accredits degree-granting postsecondary educational institutions in the United States and assesses institutions based on their mission; ethical and responsible conduct; teaching and learning quality, resources, support, evaluation, and improvement; and institutional effectiveness, resources, and planning. Learn more.

No, the transcript and diploma that MS-CS on Coursera students get is the same as the diploma for our on-campus program. There are no "online" or "Coursera" designations.

  • For-Credit Experience: You can enroll right away into a series of three 1-credit pathway courses in the Breadth requirements. No transcripts or applications are required. To get started, fill out an enrollment form during the enrollment window, select and enroll in a course(s), and pay your tuition. 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.

    In the meantime, you can explore our non-credit experience. Learn more atHow It Works.

  • Non-Credit Experience: To enroll in the non-credit versions of the MS-CS on Coursera curriculum, sign up for an account on , find the course you are interested in, and click the Enroll button to audit the course. Learn more at How It Works. We always recommend that students always work on the courses in the public, non-credit, version first then enroll for credit when they are ready to complete the course for credit toward their degree.

Please see Coursera’s list of and ProctorU's .

  • Computer: We recommend you use a laptop or desktop computer rather than a mobile device (iPhones and Android phones) or tablet (iPads and Android tablets). Some 2-in-1 or hybrid laptops (like Google ChromeBooks), Linux operating systems, Windows 10S or Surface RT, and virtual machines may not be compatible with courses that include proctored exams.
  • Internet: We recommend you use an Internet download speed of 1.5 Mbps and an Internet upload speed of 1 Mbps.
  • Browser: We recommend that you use either the Chrome or Firefox web browsers.
  • Peripherals: You will also need a webcam, which is required to verify your identity and complete proctored exams.
  • For Exams: You must test your equipment and schedule your exam proctoring session at least 72 hours in advance of your desired session. To test your equipment, take the . For more information, see the .

No. The Coursera degree and the on-campus degree are not interchangeable. If you start the Coursera degree, you cannot later switch to the on-campus program and vice versa.This program is not interchangeable with the on-campus program because of course delivery structure and differing admission requirements.

Yes, but first make sure you understand important considerations & required steps.

  • Use the MS-CS enrollment form. Indicate that you are pursuing the Degree. Choose courses that will count toward the MS-CS. Note that, of the 30 credits required for the MS-CS, you may complete up to 6 elective credits from other 񱦵 degrees on Coursera that both (a) do not have a CSCA prefix, and (b) are not cross listed with a CSCA course. All courses must be graduate level, offered on Coursera, and meet all applicable academic standards. This includes all courses offered by the ME-EM, MS-DS, or MS-EE on Coursera without a CSCA prefix, except the following four courses. Credit for the following four courses cannot be applied toward any MS-CS requirement: 
    • 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.
  • Connect with your MS-CS program to discontinue your MS-DS program.
  • Decide whether you are happy with fewer CS courses appearing on your 񱦵 transcript. 񱦵's Department of Computer Science encourages MS-CS students to take the Computer Science (CSCA) versions of cross-listed courses to ensure their transcripts reflect the substantial amount of coursework they are completing directly in their home department. Any MS-DS courses you complete will appear on your CU transcript with the Data Science prefix (DTSA).

You can earn a Data Science Graduate Certificate on your way to an MS-CS degree without needing more than 30 credits. This is possible because multiple courses in the MS-CS and MS-DS programs are cross listed. Note that you can apply credits from one course toward 1 graduate degree and 1 graduate certificate, as long as you earn the graduate certificate first.

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.

Make sure you take courses in the correct order and complete all steps to earn the certificate(s) you are most interested in. Additional steps are required to earn graduate certificates offered by 񱦵 degree programs on Coursera other than your own program. Your program’s student handbook (MS-CS | MS-DS) outlines those steps and other important considerations, including rules preventing students from double counting courses between multiple certificates.

No. Key courses in these programs overlap, and the Graduate School’s “No Double Dipping” rule prevents students from applying credit from one course toward 2 graduate degrees (or toward 2 graduate certificates).

However, you can earn a Data Science Graduate Certificate on your way to an MS-CS degree without needing more than 30 credits. See Can I earn both a Data Science Graduate Certificate and an MS-CSfor details.

This degree is self-paced. Students who take 3 courses per 8-week session (equivalent to a full-time graduate-level course load) typically complete the degree in about 2 years. However, you can take more courses per session to complete the degree more quickly. Or you can take fewer courses per session if you prefer a slower pace. Please note that you must complete all courses within 8 years.

Yes, students who successfully complete the MS-CS on Coursera degree will be invited to campus for graduation.

Yes, but first make sure you understand important considerations & required steps outlined below.

Please be aware that the MS-DS and MS-CS are different degree programs with different requirements. While the programs share a similar structure using performance-based admission, pay-as-you-go tuition, and options for both non-credit and for-credit experiences, there are also important differences. Please carefully review the following:

  • Recommended prerequisite knowledge: Though neither program has formal prerequisite requirements, they do recommend students have familiarity with particular subjects. See recommended prerequisite knowledge for the MS-DS and the MS-CS. 
  • 񱦵 requirements: See a list of admissions requirements for the MS-DS and the MS-CS.
  • Curriculum: See an outline of coursework requirements for the MS-DS and the MS-CS.
  • Grade requirements: The MS-CS requires a minimum grade of B on all breadth courses (including pathway courses) and a minimum of a C on all elective courses. If you have not earned these minimum grades in the DTSA version of a course, you will not be able to apply that credit toward the MS-CS unless you retake the course and meet this minimum grade requirement. Both programs require a 3.0 cumulative GPA and 3.0 pathway GPA. See details for both programs in the MS-DS and MS-CS student handbooks.
  • Tuition: Tuition rates vary by program. See details for the MS-DS and MS-CS.

Please be careful to indicate your degree interest properly, as noted below:

  • DO indicate degree interest on the MS-CS enrollment form. Use the MS-CS enrollment form to select, enroll in, and pay for for-credit courses. At that point, you will indicate that you are interested in pursuing a degree on the MS-CS enrollment form.
  • If you already indicated you were interested in “pursuing a degree” on the MS-DS enrollment form, you must take additional steps to change your degree. Please contact the MS-CS program if you intend to switch programs.

You will not be admitted to the MS-CS until you meet all requirements. You must meet all admission requirements outlined in the MS-CS student handbook, including completing a full pathway specialization with a B or better in each course. You will also need to indicate your intent to pursue the MS-CS degree, which you can only do on an MS-CS enrollment form. Admission decisions are released once per session, approximately 3-4 weeks after the end of the session. Admission in one porgram does not carry over to another.

We'll mail your complimentary paper diploma and/or certificate approximately eight weeks after the end of the session in which you complete your degree requirements.

You should verify both your name that will appear on your diploma, as well as the address your diploma will be mailed to in your Buff Portal. You will need to Update Your Contact Information if your name and/or home address are not listed correctly.

You also have access to a Certified Electronic Diploma & Certificate (CeDiplomas/CeCertificates). Go to the electronic diplomas & certificates card in Buff Portal and click the "Access your CeDiploma/CeCertificate" link to access CeCredential Trust, an approved third-party vendor of 񱦵. Please see CeDiplomas/CeCertificates for additional information regarding electronic diplomas.

Yes it does, it is the exact same accredited degree as the residential MS-CS degree.

Yes, the MS-CS Coursera degree is a fully accredited M.S. degree and is the exact degree as the CU-Boulder MS in CS residential program. You could apply to the CU-Boulder Ph.D. program with the MS-CS Coursera degree, and you can apply to other U.S. University Computer Science Ph.D. programs with this degree. Note that Ph.D. program admission, at CU-Boulder, or other U.S. universities evaluates many aspects of a Ph.D. applicant's application: the M.S. granting institution, the program and your GPA are academic metrics to evaluate, but an applicant's professional work history, experience, community volunteering and leadership are other factors (there are more) to take into consideration.

YES! If a student was to earn an MS-CS degree and they want to come back after they earn a degree to pursue additional classes towards a MS-CS certificate (or other CU on Coursera certificate), they can! The student can re-enroll in classes through the current student enrollment form and it will add them to a 2nd non-degree program plan and if they meet requirements for a certificate, it will be added at the end of each term. If you have already completed the courses that are needed for the AI certificate with your MS-CS degree, you will need to enroll in another AI certificate course to activate your non-degree student seeking status.

Remember, the "no double dipping rule" applies here as well. Students cannot count the same class for two degrees or two certificates. Students cannot use a class they took prior towards that certificate if it was already used for another certificate.

Eligibility & 񱦵

No. Our admissions process does not depend on your academic history. Instead, we use performance-based admissions. This means wedetermine admission based only on your performance in a set of three specialized "pathway" courses. Simply complete your chosen three-course pathway for credit with a B or better in each class to demonstrate your proficiency and be admitted to the program. Admitted students become degree seeking students and their transcript will reflect this at the next University census date after they are admitted.

There are no formal prerequisites for the MS-CS on Coursera, but you should be knowledgeable in the following subjects:

Algorithms: You must understand the concepts covered in the following courses taught by Dr. Sriram Sankaranarayanan to succeed in the pathway focusing on data structures and algorithms. We recommend completing these courses in the non-credit experience before starting that three-course MS-CS pathway; they are a great option to refresh your skills and ensure you're ready. Note that you cannot apply credit from these courses toward MS-CS graduation requirements.

  • Non-credit version of
  • Non-credit version of

Programming: You should be familiar with one or more of the following languages:

  • C, C++, or Rust - consider the following Coursera courses for more learning:
  • Python – consider 񱦵's non-credit Expressway to Data Science: Python Programming specializationif you do not feel confident in this material. If you are looking for more Python courses, you can try:
  • Java - consider the following Coursera courses for more Java learning foundations:

Math:You should have an understanding of the following branches of mathematics:

  • Linear algebra – consider 񱦵's non-credit courseif you do not feel confident in this material
  • Probability and statistics
  • Discrete mathematics
  • Consider the 񱦵

If you do not yet feel ready to complete your pathway courses and earn program admission, we suggest reviewing courses on the Coursera platform and/or enrolling in a pathway course as a non-credit learner, which gives you the option of previewing course content. Then, you can upgrade to the for-credit version and pay tuition when you are ready. Any assignments you complete in the non-credit experience will be automatically applied to your for-credit experience after you upgrade. Due to their interactive nature, discussion board posts and peer-graded assignments may not transfer from session to session when you upgrade. Be sure to save your work off-platform.

You can also consider 񱦵's Computer Science Post-Baccalaureate non-degree program to boost your foundations for the MS-CS degree. This program offers non-credit courses in all of the foundational areas fro the MS-CS program.

Yes! This 100% online program is open to learners around the world. However, due to current restrictions imposed by the U.S. Department of Treasury’s Office of Foreign Assets Control (OFAC), neither 񱦵 nor Courseracanprovide online courses to the following countries: Cuba, Iran, Sudan, North Korea, Syria, and the Crimea Region of Ukraine.

There is an inherent risk in enrolling in any U.S. university remotely. Students living outside the United States—especially in countries where OFAC has issued (e.g., the Russian Federation)—should note that, in the unfortunate event that sanctions are elevated, there is a possibility they would not be able to complete their degree. While OFAC can issue that authorize U.S. universities to offer otherwise prohibited online education despite elevated sanctions, these licenses are not guaranteed and U.S. universities could be required to stop offering online coursework to new and existing students at any time in order to comply with updated federal regulations.Learners in some locations may encounter IP or payment purchase blocks when attempting to enroll in or access courses on Coursera. See the 񱦵's Office of Export Controls'and for details.

You do not need to submit anything. This program uses performance-based admissions, which means you earn program admission simply by performing well in a three-course pathway. We never ask for transcripts, test scores (like GRE or TOEFL), essays, letters of recommendation, or application fees.

Simply enroll in and complete your chosen three-course pathway with a grade of B or better in each course to demonstrate your proficiency and be admitted to the program. Pathway courses are a required part of the curriculum, which means you make direct progress toward your degree while you work toward program admission.

No. Because this program uses performance-based admissions, we never ask for transcripts, test scores (like GRE or TOEFL), essays, letters of recommendation, or application fees. Rather, you earn program admission simply by performing well in our "pathway" courses.

Simply enroll in and complete your chosen three-course pathway with a grade of B or better in each course to demonstrate your proficiency and be admitted to the program as a degree-seeking student. Pathway courses are a required part of the curriculum, which means you make direct progress toward your degree while you work toward program admission.

No. Because this program is entirely online, students are not eligible for a student visa (e.g., F-1 or J-1 visa) or Form I-20. Students who are already in the US on an H1-B visa must work with their sponsor to determine if they are eligible to participate in this correspondence course.

Reach out to the MS-CS program if you want to transfer to the MS-CS program and if you have questions about your previously completed CU on Coursera courses applying to your MS-CS degree.

Up to 6 graduate-level credits from select courses offered by other CU degrees on Coursera to be applied toward the MS-CS on Coursera degree. See the Curriculum page for details.

After you enroll in and successfully complete your chosen three-course pathway with a grade of B or better in each course, you will be automatically admitted to the program as a degree-seeking student. All admitted students receive an official offer letter via email -3 to 4 weeks after the session ends. Admitted students become degree seeking students and their transcript will reflect this at the next University census date after they are admitted.

After admission to the degree, your cumulative GPA will include all attempted for-credit coursework. This includes any courses you failed before gaining admission to the degree. However, you are allowed to retake your original pathway courses and try to improve your grade. See the MS-CS on Coursera Student Handbook for details about course repetition and grade replacement.

Your mathmatics background should include, at least, mathematics at the level of sophistication of calculus or above. Examples of such courses such are calculus, differential equations, linear algebra, probability, statistics and abstract algebra.Your knowledge and comfort level should indicate that you have achieved mathematical maturity expected in science, engineering, or mathematics. These courses are helpful if you are concerned about your math preparedness:

  • Linear algebra – consider 񱦵's non-credit courseif you do not feel confident in this material
  • Probability and statistics
  • Discrete mathematics
  • Consider the 񱦵

Coursework

A course is a collection of on-demand videos, discussions, readings, and assignments designed by a 񱦵 instructor to help you learn more about a specific, focused topic.

Each course offers both a non-credit experience and a for-credit experience. See How It Works for more details about the differences between these options.

A specialization consists of three 1-credit courses linked together to cover a topic more fully. In general a 3-course specialization is the equivalent of what would be covered in a 3-credit, 16 week course on-campus.

Pathways are a series of three 1-credit courses within the Breadth requirements of the degree. Together they make up a pathway. Complete your pathway with a grade of B or better in each course to be admitted to the program.

Review the curriculum and degree requirements to learn more about Pathway specialization courses in the Breadth requirements.

Yes, all students must complete the courses in both pathways to complete the degree. To gain admission, you only need to complete one pathway, and you can choose the pathway that is right for you.

Note that you cannot "mix and match" pathways to earn program admission. You must complete all three courses within one pathway to gain admission. You cannot, for example, complete 2 courses from one pathway specialization and 1 course in the other pathway specialization to earn admission.

No, you may complete courses in any order.We recommend you complete each specialization course in the order they are listed, but you may choose to follow a different order if you wish.

Please note that to be formally admitted to the program, you must complete a pathway with a B or better in each class. If you have already completed coursework in a CU on Coursera degree program and have received academic credit for your work prior to completing a pathway, your allowable completed credits will be applied to your degree progress and academic transcript once you are formally admitted.

No. The degree is designed to be flexible. You may complete courses in any order. We recommend you complete each specialization course in the order they are listed, but you may choose to follow a different order if you wish.

If you are concerned about the level of coursework and your preparation to be successful, we highly recommend starting all of your courses in the public, non-credit version. 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 the account linking and onboarding, the progress you made on the coursework in the public version will transfer into the for-credit version.

You will complete 15 credits of breadth coursework across two pathways and three specializations in data structures and algorithms, machine learning, ethics and computing, and systems. You will also earn 15 credits of elective coursework across your choice of a variety of topic areas, including human-computer interaction, autonomous systems, data mining, natural language processing, software architecture, and more. You must complete at least four full elective specializations.

From CU Programs on Coursera: Yes, up to six graduate-level credit hours of courses from other CU programs on Coursera may be applied as elective credits toward the MS-CS degree on Coursera. All courses must be graduate level, offered on Coursera, and meet all applicable academic standards. This includes courses offered by the , , and programs on Coursera that do not start with a "CSCA" prefix.

NOTE: Credit from these courses cannotbe 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 - 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 may not be counted twice 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 particular course toward two graduate certificates or two graduate degrees. CU certificates on Coursera are automatically awarded once all requirements are met.

From Other CU Programs: No, this program does not currently accept transfer credit from CU programs other than those listed above.

From Other Institutions: No, this program does not currently accept transfer credit from other institutions or from 񱦵 programs other than those listed below.

A cross-listed course is offered under two or more 񱦵 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 the MS-CS on Coursera 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.

Yes. Cross-listed courses are considered equivalent when evaluating graduation requirements. You can identify cross-listed courses by checking the MS-CS on Coursera Student Handbook.

An outside elective (sometimes called an “external” elective) is a course offered by another 񱦵 degree program on Coursera. You may apply credits earned from outside elective courses to complete your degree’s elective requirements. Acceptable outside electives are available in the MS-CS enrollment form and labeled in the Outside Electives section of the form. Tuition rates vary by program. Credit limits apply and not all courses are applicable to all degree programs. See the MS-CS on Coursera 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 CSCA coursesby checking the MS-CS on Coursera 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.

Find MS-CS on Coursera courses and view course details on the Curriculum page. You can also visit the and navigate to the .

After you have enrolled for credit and become a 񱦵 student, you have access to your Degree Audit in your Buff Portal (student portal). Your degree audit will list your degree requirements, the courses and milestones completed and your catalog year.

For-credit courses are open for 8 weeks. All for-credit coursework is due by the last day of the 8-week session. There are 6 enrollment sessions per year. Each enrollment window starts 2 weeks before the first day of class and ends 2 weeks before all coursework is due. See the calendar for exact dates.

Non-credit courses do not have time limits. They are not tied to sessions and can be completed entirely at your own pace. See How It Works for details.

This degree is self-paced, and there is no minimum or maximum number of courses required per session. We recommend new students take one class in their first session as they adjust to the demands of this graduate-level program. We recommend students take up to 3 courses in subsequent sessions, which is equivalent to a full-time graduate-level course load. Students who take 3 courses per session complete the degree in about 2 years. You must complete all courses within 8 years.

Courses are self-paced; however, all for-credit coursework must be submitted by the last day of the 8-week session.

For every one credit hour you take, you may spend 5–8 hours per week depending on your knowledge and skills. This includes videos, discussions, readings, and assignments.

Lectures are recorded on video and available on-demand. You do not need to worry about attending a live lecture in a different time zone.

Instructors create videos specifically for Coursera. These lectures are designed with online learners in mind and not simply recordings of on-campus classes.

No. Cross-listed courses are considered equivalent to each other when evaluating graduation requirements. They do not count toward your limit of “outside” elective courses. Please see What is a cross-listed course for important details.

There may be group work. Assignments vary by course and may include individual and group work assignments.

Courses may include project-based assessments and/or online proctored exams that use ProctorU, an online proctoring service that ensures exam integrity and accountability. ProctorU requires a computer, Internet connection, and webcam and monitors students in three ways:

  • By using secure identity verification to ensure that the person taking the test is the correct student
  • By employing a human proctor to monitor the test taker through a webcam. You will be connected to a real person to guide you through the process
  • By employing a proctor to watch the test-taker’s screen in real-time, allowing them to see everything the student is doing

ProctorU is available 24/7. However, you must test your equipment and schedule your proctoring session at least 72 hours in advance of your desired session. To test your equipment, take the . See the for more information.

Currently there are 2 courses in the MS-CS degree curriculum that use ProctorU for exams. These courses are:

No, the MS-CS on Coursera is a non-thesis degree that requires 30 credit hours of coursework only. Other institutions and universities may accept transfer credit from the MS-CS on Coursera program at their discretion.

The degree does not currently include a capstone project.

For-credit Courses:

  • If you have accessed restricted content (usually a final exam or project), you will receive a letter grade for the course based on the work you completed before the end of the session. This includes a final exam/project grade—even if you did not finish that assignment.
  • If you have not accessed restricted content and not received a course grade, you can drop or withdraw from a course depending on your timeline. See the Registrar's Special Programs page for information and forms related to drops, refunds, and withdrawals.
  • If you do not unlock the restricted content you will be administratiely withdrawn from the course. If you do not plan to drop or withdraw, and you want credit for your course toward your degree, you must unlock the restricted content (complete the password quiz for the final).
  • Tuition payments cannot be rolled over to future sessions.

Non-credit Courses: Non-credit courses have no time limit.

Required assignments may include peer reviews. There are two parts to peer-graded assignments:

  1. You must submit your own assignment, which will be graded by your peers.

  2. In turn, you are required to grade a minimum number of your peers' submitted assignments. This must be completed 3 days before the last day of class in order to receive a grade for your own assignment.

When grading your peer’s work, you will be provided a rubric, which clearly describes the assignment components and the type of responses that correspond to each possible grade. Rubrics are used to ensure grading consistency; they also help learners understand the expectations of each assignment.

Peer reviews are a part of this program and some courses have Peer Review Assesments. As you work on these assignments, please keep the following expectations and guidelines in mind:

  • Most peer review assignments are due 3 days before the end of the session. This deadline ensures there is enough time for your submissions to accrue all required reviews. Keep this in mind as you work through the course.

  • Some peer review assignments will require 1-3 reviews before you receive a grade. Please note if you do not receive all required reviews before the end of the session, your course facilitator will review your work and provide a grade.

  • These assignments are designed to provide you an opportunity for professional practice. Think of your peers as your colleagues and craft your responses to communicate your work in a way that is clear and easy to understand.

  • When reviewing your peers' work, practice reviewing the way you would for colleagues in your professional setting.

  • Some courses in the program have chosen to allow reviewers to remain anonymous. However, in the spirit of thinking of your peers as colleagues, some courses do allow learners to see who reviewed their work.Please refer to the assignment details or ask your Course Facilitator if you have questions.

  • Finally, you are responsible for reviewing your peers' work thoroughly. This includes continuing to interact with course materials and building your abilities to make sense of your peers' submissions, code, and visualizations throughout the program.

Grades

Students who are worried about succeeding in a particular class have multiple options to consider, depending on the exact circumstances. Options include:

  • Previewing a non-credit version of the course beforehand to get a head start
  • Attend weekly office hours with the course facilitator (for-credit courses only)
  • Connect with peers in Slack for support (for-credit courses only)
  • Connect with peers in discussion forums for support
  • Dropping or withdrawing from the course
  • Grade replacement
  • Pursuing a different pathway (before degree admission)

If you do not complete each pathway course with at least a B grade or do not earn at least a 3.00 GPA average for the pathway, you can pursue another pathway. If you successfully complete this second pathway, you will be admitted to the degree program.

To successfully complete a pathway and earn admission to the program, you must:

  • Earn at least a grade of B in each pathway course
  • Maintain a 3.00 average GPA (or higher) for your pathway courses
  • Maintain a 3.00 cumulative GPA (or higher) for all for-credit courses taken to date
  • Declare your intent to pursue the degree when you enroll in classes

You can also preview the second pathway option as a non-credit learner, and then upgrade to for-credit when you are ready to pay tuition and complete the final exam.

After admission to the degree, your cumulative GPA will include all attempted for-credit coursework. This includes any courses you failed before gaining admission to the degree. However, you are allowed to retake your original pathway courses and try to improve your grade.

Before the MS-CS degree is awarded, students must have a minimum cumulative GPA of 3.00 and a grade of B or better in each breadth course (including the two required pathways and three required breadth specializations). Elective courses in which grades below C (2.0) are received may not be applied toward degree requirements.

See the MS-CS on Coursera Student Handbook for details about course repetition and grade replacement.

Yes, you must maintain a 3.00 average throughout the program to remain in good academic standing. The MS-CS degree cannot be awarded until you have achieved a minimum 3.00 cumulative GPA, and a grade of B or better in each breadth class (including the two required pathway specializations and the three additional required breadth specializations). Elective courses in which grades below C (2.0) are received may not be applied toward degree requirements.

See the MS-CS on Coursera Student Handbook for details, including what happens if your cumulative GPA falls below 3.00.

MS-CS students must earn a B or better in their Breadth courses. If a student earns a B- they must still retake the course and earn a better grade to recieve credit for the course toward their degree requirements. A grade of B- does NOT qualify for grade replacement. This means that both attempts will post to your transcript and both grades will factor into your GPA.

Please contact your course facilitator and/or advisor if you are concerned about not meeting the minimum required grade in your courses.

Non-credit vs. For-credit Experiences

Our non-credit experience includes:

  • Flexible dates – complete coursework at your own pace
  • Coursera completion certificates, which do not imply the conferral of credit from CU
  • Coursera subscription fee – certain courses may be free with trial or course audit
  • Independent work
  • Coursework that transfers after upgrading to the for-credit experience
  • Easy enrollment process
  • Ability to upgrade, pay tuition, and complete additional coursework at any time to earn CU credit

Our for-credit experience includes:

  • Set session dates – six 8-week sessions per year
  • CU credit, stackable toward CU graduate degree
  • Pay-as-you-go tuition
  • Access to additional academic support from CU course facilitators
  • Access to online CU services, including CU on Coursera membership, alumni services, and a student email address
  • Access to additional coursework and materials
  • Simplified enrollment
  • Performance-based admission

Learn more on our How It Works page.

To enroll in the for-credit versions of courses

  • Click the Enroll Now button during an open enrollment period
  • Complete the registration form for 1–3 courses (the form will limit you to 3 courses per form, you cna submit several forms per enrollment session)
  • Pay your tuition
  • Check your email for next steps
  • Complete all coursework by the end of the 8-week session to earn CU credit

Once you have enrolled in a for-credit course and paid your tuition…

  • You will receive two emails from 񱦵: one confirming your enrollment and one with information about your new 񱦵 email address and student ID, or IdentiKey.
  • You will also receive an email from Coursera with instructions on how to create a Coursera account and/or link your Coursera account to your new 񱦵 account using your IdentiKey.
  • Prior to accessing for-credit MS-CS on Coursera content for the first time, you must activate/link your student accounts and pass a free non-credit onboarding course (3–5 hours). You only need to complete these steps once.

You must complete all coursework by the end of the 8-week session to earn CU credit.

No, the non-credit courses carry a monthly subscription fee, which you will pay to Coursera rather than to the 񱦵. However, some courses offer a free trial period.

To enroll in the non-credit versions of courses:

  • Sign up for an account on
  • Find the course you are interested in
  • Click the Enroll button

Once you enroll, you will be able to either audit the course for free or pay a certificate fee to earn a Course or Specialization Certificate. Some courses offer a free trial during which you can try out the course for free before committing to paying the certificate fee.

Upgrade, pay tuition, and complete additional coursework at any time to earn CU credit for the course.

You may upgrade from non-credit to for-credit at any time during the enrollment window using the . Each enrollment period starts 2 weeks before the first day of class and ends 2 weeks before all coursework is due.

All for-credit coursework is due before the last day of the session, peer-reviews are due 3 days before the last day. Previously completed assignments will be automatically applied to your for-credit experience when you upgrade from the non-credit experience.

Please note that if you start a non-credit course within the same month that you upgrade to the for-credit version, you will not receive a refund for the monthly subscription associated with the non-credit course. The monthly subscription fee is paid to Coursera, not to the 񱦵.

No. The work you complete in the non-credit version of a course transfers over to the for-credit version when you upgrade and pay tuition. Due to their interactive nature, discussion board posts and peer-graded assignments may not transfer from session to session if you drop/withdraw and later re-enroll in a particular class. Be sure to save your work outside of the Coursera platform.

You can upgrade from non-credit to for-credit at any time during your learning journey. After you upgrade, you will complete additional coursework (usually a final project or exam) to earn credit for the course. You have up to 8 years to complete the full program.

If you are taking a non-credit class, you only pay the monthly Coursera subscription fee.

If you are taking a for-credit class, you only pay the $525per credit hour tuition fee.

If you start a non-credit course within the same month that you upgrade to the for-credit version, you will not receive a refund for the monthly subscription associated with the non-credit course. The monthly subscription fee is paid to Coursera, not to the 񱦵.

Yes, students can earn a Course Certificate from Coursera for non-credit courses and specializations. This non-credit certificate of completion does not earn transcripted credit from the 񱦵, nor can it be applied to the degree.

Yes, you can always start with a non-credit version of a course on Coursera and later upgrade to the for-credit version and pay 񱦵 tuition. We recommend starting all of your courses in the non-credit version, no matter your degree progress. Then, enroll for credit when you are ready to complete the course for credit toward your degree.

Artificial Intellgence Graduate Certificate

If you select the following specializations* for your AI certificate, you will have completed 40% of your MS-CS degree:

  • Machine Learning
  • Computing, Ethics and Society
  • Foundations of Autonomous Systems
  • Introduction to Robotics with Webots

*based on specializations available by launch of the certificate in Fall 2024

No. Because Machine Learning is a required Breadth specialization for the MS-CS degree and you cannot apply the same credits to 2 of the same level of credentials, so you will need to apply the Machine Learning specialization to the AI certificate if you plan to earn the MS-CS degree, the DS certificate and the AI certificate. You will end up with 3 extra credits when earning all three; the MS-CS degree, AI Certificate andDS Certificate. You willnotwant to select Machine Learning as one of yourDS certificate electivesif you plan to earn all three of these.

Yes! The AI Graduate Certitificate prepares engineers, applied scientists, and technical professionals for career advancement in advanced technical and technical leadership roles. Curriculum addresses a range of areas including theory, software, systems, machine learning, and ethics. The graduate certificate in AI will provide students a strong foundation in key AI topics.

Students will apply Machine Learning (ML) algorithms to real world data sets; examine ethical issues in the design and implementation of current and future computing systems and technologies; create an appreciation for the tight interplay between mechanism, sensor, and control in the design of robotic and intelligent systems; and provide a comprehensive exploration of Generative AI. Future courses in reinforcement learning, natural language processing, and autonomous systems will round out the curriculum.

Yes! If a student was to earn an MS-CS degree and they want to come back after they earn a degree to pursue additional classes towards a MS-CS certificate (or other CU on Coursera certificate), they can! The student can re-enroll in classes through the current student enrollment form and it will add them to a 2nd non-degree program plan and if they meet requirements for a certificate, it will be added at the end of each term.

Remember, the "no double dipping rule" applies here as well. Students cannot count the same class for two degrees or two certificates. Students cannot use a class they took prior towards that certificate if it was already used for another certificate.

If you are are student that will complete all degree requirements in Summer 2 (before the certificate launches in Fall 2024) your MSCS degree will be conferred. You can re-enroll as a nondegree student, using the MS-CS form in Fall 2024 in your remaining required classes for the certificate, or if you have completed all classes for certificate prior, you will have to enroll in a different MS-CS class that is also in the certificate program, in Fall 2024.

Course release dates will be posted next to the course when the availability of enrollment is confirmed. To avoid any confusion we will not provide estimated release timelines.

Please use theand select your courses you want to apply toward your certificate. When you get to the "Educational Interest" section of the form, please select "Pursuing a Graduate Certificate". You must complete this step if you are also earning your MS-CS degree in paralell with the certificate when you enroll in at least one course that applies to both.

Yes. When you take a course for-credit it will appear on your official transcript.

We'll mail your complimentary paper certificate approximately eight weeks after the end of the semester in which you complete your certificate requirements.

You should verify both your name that will appear on your certficiate, as well as the address your certficiate will be mailed to in yourBuff Portal. You will need toUpdate Your Contact Informationif your name and/or home address are not listed correctly.

You also have access to a Certified Electronic Certificate (CeDiplomas/CeCertificates). Go to the electronic diplomas & certificates card in Buff Portal and click the "Access your CeDiploma/CeCertificate" link to access CeCredential Trust, an approved third-party vendor of 񱦵. Please seeCeDiplomas/CeCertificatesfor additional information regarding electronic diplomas.

Finances

See the MS-CS on Coursera Bursar page for program specific cost information.

Because this program is 100% online, the tuition is the same for all students regardless of where they live.

No. Because this program is 100% online, the tuition is the same for all students regardless of where they live.

No, this program does not currently have any student fees. When you enroll in for-credit courses and pay CU tuition, you do not need to pay for a Coursera subscription or cover exam proctoring costs. Your tuition also includes access to CU on Coursera, Digital Library resources, the Handshake online employment platform and networking tool, and the Forever Buffs alumni association. See more "Resources and Links" on the Current Students page.

No. If you are taking a non-credit class, you only pay the monthly Coursera subscription fee.If you are taking a for-credit class, you only pay the $525 per credit hour tuition fee.

Please note that if you start a non-credit course within the same month that you upgrade to the for-credit version, you will not receive a refund for the monthly subscription associated with the non-credit course. The monthly subscription fee is paid to Coursera, not to the 񱦵.

Please refer to the information on the Finances page.

See the Bursar's Degrees on Coursera page for details.

MS-CS on Coursera courses use pay-as-you-go tuition, where payment is due at the time of enrollment. You must make a tuition payment to complete the enrollment process, which is different from our traditional on-campus programs.

Once you are registered, you can submit a voucher or letter of authorization from your company detailing your student information, the charges and courses covered, and the period that will be covered. About 1–2 weeks after we receive your completed form, we will refund your pre-pay payment and submit an invoice to your sponsor. See more about the sponsorship process.

No, tuition payments cannot be rolled over to future sessions.

No. When you pay 񱦵 tuition for a for-credit course, you do not need a Coursera subscription. However, non-credit courses carry a monthly subscription fee. This means that if you start in the non-credit version of a course on Coursera and later upgrade to the for-credit version, you will also have paid Coursera's monthly subscription fee.

You pay per credit hour. You may drop a class if both of the following conditions are met:

  • You are within 14 days from the class start date or enrollment date (whichever is later).
  • You have not accessed restricted content in the course.

See the Registrar's Special Programs page for more information.

No, this program is not eligible for the University of Colorado employee tuition assistance benefit.

This program is eligible for education benefits offered through Veteran’s Affairs (VA). Check with your VA advisor and visit the for more information. Please contact MS-CS staff at mscscoursera-info@colorado.edu for more information.

񱦵 Resources

Course facilitators hold weekly office hours so you can connect with them and ask questions about the material being covered in the program.

There are not currently opportunities for local students in the online program through Coursera to meet with professors.

Tutors are not available at this time. We highly encourage you to work with your peers.

MS-CS on Coursera students do not have access to campus facilities, but can access online resources including CU on Coursera, off-campus digital library resources, Handshake and virtual career services, and the Forever Buffs alumni association. Students can also get a Buff OneCard studnet ID card. Students that get their Buff OneCard are eligible to purchase a "Student Affiliate - No Fees" membership at the Rec center on campus. The memebrship is for Fall and Spring only.

Yes, students taking for-credit classes receive an IdentiKey, which includes your 񱦵 login name and password. Your IdentiKey uniquely identifies you and acts as your student identification number. Students can alsoreceive a physical Buff OneCard (student ID card) for $30 by emailing a headshot, photo ID, and mailing address to boc@colorado.edufrom your colorado.edu student email address.

Yes, students taking for-credit classes receive an official @colorado.edu email address. It is required that you activate your CU student email account as all communications will be sent to this email address. You will need to check your coloraod.edu email address regularly.

Careers in Computer Science

No, internships are not currently available as part of this program.

Students who have been admitted into the MS-CS on Coursera degree program will have lifelong access to Handshake through 񱦵 Career Services. Handshake is an online employment platform where employers post jobs and hold virtual events. Alumni can also use Handshake as a networking tool to connect with other alumni.

Admitted students also get access to AI Resume Builder by Quinncia. This tool leverages data-science, machine learning, and natural language processing to provide personalized feedback on your resume based on criteria gathered from employers and global best practices.

As a 񱦵 graduate, you will join the alumni association Forever Buffs.

Computer science MS graduates typically hold positions as software engineers, software developers, systems engineers, cloud architects, research scientists, research engineers, security engineers, information security analysts, user interface (UI) engineers, user experience (UX) researchers, interaction designers, computational scientists, computational engineers, data scientists, data architects, data analysts, front-end developers, and full-stack developers.

With an anticipated 25% job growth by 2031, the field is expecting “much faster than average” year-over-year growth for 2021-2031. []

񱦵 MS-CS alumni are employed across a variety of organizations and sectors. US-based graduates from the 񱦵 MS-CS on campus work for giants like Google, Microsoft, Amazon, Facebook, Adobe, Lockheed-Martin, IBM, Salesforce, and Accenture, as well as start-up companies of all sizes. Popular sectors include information technology, aerospace, finance, manufacturing, consulting, and government laboratories.

With a nationwide average salary of $132,930 [], computer scientist salaries are more than double the average salary across sectors. Computer science graduates out-earn all other MS degree holders in the United States [].

Help

Ifyou are enrolled in a for-credit course and are having difficulties with your final exams, please email us at mscs-coursera@colorado.edu.