��«����Ƶ

Yes, the online MS-DS program falls under the ��«����Ƶ's overall accreditation by the Higher Learning Commission (HLC) and was approved by the Colorado Department of Higher Education (CDHE).

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

You can enroll right away into a series of 3 one-credit pathway courses with a focus on either statistics or computer science. No transcripts or applications are required. To get started, to select and enroll in a pathway course and pay your tuition.

To enroll in the non-credit versions of the MS-DS curriculum, sign up for an account on , find the course you are interested in, and click the Enroll button to audit the course.

No, the MS-DS is a non-thesis degree that requires 30 credit hours of coursework only.

The degree does not currently include a capstone project.

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 online MS-DS degree will be invited to campus for graduation. For more information about graduation, please see the Current Students page.

Degrees are conferred three times annually. Check the graduation calendar for semester-specific dates. Diplomas will be issued electronically. Paper diplomas are available upon request for a small fee. See Order a Diploma or Certificate.

Students who graduate from the program and earn the MS-DS degree are welcome to attend on-campus graduation ceremonies but are not obligated to do so.

This program is designed for working professionals in the industry. It is not intended to train Ph.D. students or research students. Other institutions and universities may accept transfer credit from the online MS-DS program at their discretion.

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-CS for details. 

The Data Science Certificate is a 12-credit credential, whereas the Master of Science in Data Science is a 30-credit credential. The certificate is built into the degree, so as long as the 3.0 GPA requirement is met within the certificate courses, students will automatically earn the certificate on their way to earning the full degree. Students can choose to only complete the certificate. 

Please note: The Data Science Certificate is different than the Coursera completion certificate that students earn when successfully completing a course on Coursera.

Unlike other data science programs, the Coursera program at CU ��«����Ƶ provides students with end-to-end data experience, including data mining, cleaning data, data modeling, data analysis, and how to visualize and communicate data. Students in this program understand data from Python and R perspectives and are prepared for roles such as "data analyst" and "data scientist."

Yes. Students need to complete degree requirements within 8 years (including the pathway courses), but within that time you can take breaks during 1 or more sessions, consecutively or non-consecutively. However, students admitted to the degree program who have not enrolled for two years will be discontinued until they enroll in a new for-credit course.

Coursera students do NOT have to provide any immunization proof. That is because immunization proof is only necessary for students physically on our campus in ��«����Ƶ, Colorado. You can ignore or delete emails received about proof of immunization if you are not and will not be living in ��«����Ƶ, Colorado or studying on our campus.

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

• Python 
• R programming 
• Calculus including derivatives and integrals
• Linear algebra including matrix multiplication, matrix inversion and solving linear systems using matrices
• Statistics

Complete your pathway with a 3.0 GPA average or better to demonstrate your proficiency and be admitted to the program. 

If you do not yet feel ready to complete your pathway courses, we suggest reviewing courses on the Coursera platform and/or enrolling in a pathway specialization 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.

There are no formal prerequisites for the MS-DS. However, you should be knowledgeable in the following:

• Python 
• R programming 
• Calculus including derivatives and integrals
• Linear algebra including matrix multiplication, matrix inversion and solving linear systems using matrices
• Statistics

You must complete your pathway courses with a 3.0 GPA average or better to demonstrate your proficiency and be admitted to the program.

If you would like to brush up on your programming skills, we recommend that you try the following:

• R Programming:  
• Python Programming:
• Math Topics:
• Statistics and Probability:

If you are not sure if you are ready to complete your pathway courses, we suggest reviewing courses on the Coursera platform. You can enroll in a pathway specialization as a non-credit learner, which gives you the option to preview 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.

No. This program uses performance-based admissions, which means you must complete 3 pathway courses for credit with a 3.0 GPA average or better. This demonstrates your proficiency and allows you to be admitted to the program.

Yes. This program is delivered 100% online. 

Due to current restrictions imposed by the U.S. Department of Treasury’s Office of Foreign Assets Control, webcourse delivery cannot be provided to the following areas: Cuba, Iran, Sudan, North Korea, Syria and the Crimea Region of Ukraine.

You do not need to submit anything. Because this program uses performance-based admissions, you do not need to submit transcripts, test scores (like GRE or TOEFL), essays, or even an application fee. You must complete 3 pathway courses for credit with an average GPA of 3.0 or better to demonstrate proficiency and be admitted to the program.

Yes! The MS-DS on Coursera is open to students around the world. However, due to current restrictions imposed by U.S. Department of Treasury’s Office of Foreign Assets Control, we cannot provide online courses to the following countries: Cuba, Iran, Sudan, North Korea, Syria, and the Crimea Region of the Ukraine. See CU Online Course Delivery Restriction for details.

No. To be admitted to the MS-DS as a degree-seeking student, you must enroll in and complete your pathway with a 3.0 GPA or better. Your pathway is a series of 3 one-credit courses with a focus on either statistics or computer science – you choose the pathway that is right for you. The courses in your pathway are part of the required curriculum, so you make direct progress toward your degree as you complete your pathway.

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 need to work with their sponsor to determine if they are eligible to participate in this correspondence course.

You must reach out to the Registrar at reg-specialprograms@colorado.edu to request that you be changed to an MS-DS student. This is an important step to ensure you are able to enroll in classes, earn admission to the MS-DS degree program, and receive Data Science communications.

Remember that only MS-DS courses count toward the MS-DS degree. Other CU classes on Coursera (like MS-EE courses) do not count toward 30 credits needed to earn the MS-DS degree.

Yes, you must maintain a 3.00 average throughout the program to remain in good academic standing. The MS-DS degree cannot be awarded until the minimum 3.00 cumulative GPA has been achieved. See the MS-DS Student Handbook for details, including what happens if your cumulative GPA falls below 3.00.

Students who are enrolled in for-credit courses offered by the Master of Science in Data Science program at the ��«����Ƶ are granted the same rights and have the same responsibilities as any other graduate student, regardless of age. Therefore, it is required that you, as an underage student, along with your parent/legal guardian, review the information listed below and sign the acknowledgement indicating that you understand and accept responsibility for the decision to enroll. Students under the age of 18 must have a parent or guardian sign the MSDS Underage Agreement & Acknowledgement Form. If you are an emancipated minor, please contact msds-support@colorado.edu for support. 

Converting Percentage (%) to Letter Grade (A–F)

You can find the grading breakdown for each course on Coursera. Simply go to the course in question, find the Reading: Syllabus item (usually in Week 1), and then scroll down to the section outlining the uniform letter grade rubric for that class.

Converting Letter Grades (A–F) to the 4.0 Scale

You can convert letter grades to the 4.0 scale with the CU Transcript Key. Note that the Numeric Grades (Law) column there only applies to Law School classes and is unrelated to the MS-DS.

A specialization consists of 3 one-credit courses linked together to more fully cover a topic.

We recommend you complete courses using one of our two Recommended Learner Journeys; however, you may complete courses in any order. Please note that to be formally admitted to the program, you must complete a pathway specialization with a 3.0 GPA or better. If you have already completed coursework and have received academic credit for your work prior to completing a pathway, your 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 will complete 21 credits of core coursework in statistics, computer science, and general core concepts as well as 9 credits of elective coursework. You may complete courses in any order, but we recommend following one of our two Learner Journeys.

For every one credit hour you take, you may spend 4–6 hours per week depending on your knowledge and skill. This includes videos, discussions, readings and assignments.

This degree is self-paced, and there is no minimum number of courses required per session. Students are allowed to take up to 15 credits per term (for example, a term equals spring 1 session + spring 2 session). We recommend new students take one class in their first session as they adjust to the demands of this graduate-level program. In subsequent terms, we recommend students take 3 or fewer courses per session, 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.

Look for the graduation cap icon and “Part of the Master of Science in Data Science degree” on Coursera’s . Remember that only courses with this notation fulfill MS-DS degree requirements. Other CU classes on Coursera (e.g., those offered in the MS-EE degree) do not count toward 30 credits needed to earn the MS-DS degree.

See Curriculum to find MS-DS courses and view course details.

Pathways are a series of three 1-credit courses with a focus on either statistics or computer science. Complete your pathway with a 3.0 GPA or better to be admitted to the program.

Choose one of the following pathways:

Data Science Foundations: Statistical Inference

• ​Probability Theory: Applications for Data Science (1 credit)
• Statistical Inference for Estimation in Data Science (1 credit)
• Statistical Inference & Hypothesis Testing for Data Science Applications (1 credit)

Data Science Foundations: Data Structures & Algorithms

• Algorithms for Searching, Sorting & Indexing (1 credit)
• Trees & Graphs: Basics (1 credit)
• Dynamic Programming, Greedy Algorithms (1 credit)

Yes, all students must complete the courses in both the Data Science Foundations: Statistical Inference pathway and the Data Science Foundations: Data Structures & Algorithms pathway 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. Start with the Data Science Foundations: Statistical Inference pathway if you are strong in statistics. Start with the Data Science Foundations: Data Structures & Algorithms pathway if you are strong in computer science.

Note that you cannot "mix and match" pathways to earn program admission. You must complete all 3 courses within one pathway to gain admission. (E.g., you cannot complete 2 courses in the Data Structures & Algorithms Pathway and 1 course in the Statistical Inference for Data Science Pathway to earn admission.)

If you do not complete each pathway course with at least a C grade or do not earn at least a 3.0 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 C in each pathway course 
• Maintain a 3.0 average GPA (or higher) for your pathway courses
• Maintain a 3.0 cumulative GPA (or higher) for all for-credit courses taken to date
• Declare your intent to pursue the degree when you enroll for 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 exams.

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-DS Student Handbook for details about course repetition and grade replacement.

After you pass 3 courses in one of our pathway specializations with a 3.0 GPA or higher, you will automatically be admitted to the program. All admitted students receive an official offer letter via email.

Courses are open for 8 weeks. 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. All for-credit coursework is due by the last day of the 8-week session.

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

Non-credit courses

Non-credit courses have no time limit.

For-credit courses

If you have accessed restricted content (usually the final exam), you will receive a letter grade for the course based on the work you completed before the end of the term. This includes an exam grade—even if you did not finish the exam. 

If you have not accessed restricted content nor 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 withdrawal.

Tuition payments cannot be rolled over to future sessions. 

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.
• A proctor watches the test-taker’s screen in real-time and can 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 . For more information, see the .

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
• Course repetition 
• Grade replacement (admitted degree students only)
• Pursuing a different pathway (before degree admission)

Please see Options for MS-DS Students Worried Course Grades for an outline of the above options. The MS-DS Student Handbook has more details.

Yes, 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.

No, instructors create videos specifically for Coursera. These lectures are designed with online learners in mind.

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

An outside elective (sometimes called an “external” elective) is a course offered by another CU ��«����Ƶ 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 the MS-DS 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 DTSA courses by checking the MS-DS 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.  

In order to apply outside electives to your MS-DS degree, please fill out the  survey that you will receive in your student email account approximately two weeks before the end of each session.

• Please note that 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. 
• Please complete the survey ONLY if you have completed/will complete the outside electives you would like to apply in a previous session, or in the current session. 
• You can expect to see outside electives applied to your Degree Audit (found in ) in the two weeks after official grades post.
• You must earn a passing grade, a 'C' grade or better, in outside electives to fulfill MS-DS degree requirements.

A cross-listed course is offered under two or more CU ��«����Ƶ 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-DS 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-DS on Coursera Student Handbook. 

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. 

From CU Programs on Coursera: Yes, you can apply up to six graduate-level credit hours of select courses offered by other CU ��«����Ƶ degrees on Coursera as elective credits toward the MS-DS on Coursera degree. All courses must be graduate level, offered through Coursera, and meet all applicable academic standards. Select courses include:

The following courses from the ME-EM on Coursera:

•  Project Management: Foundations and Initiation
•  Project Management: Project Planning and Execution
•  Project Management: Agile Project Management
•  Finance for Technical Managers: Product Cost and Investment Cash Flow Analysis
•  Finance for Technical Managers: Project Valuation and the Capital Budgeting Process
•  Finance for Technical Managers: Financial Forecasting and Reporting

Courses from the MS-CS on Coursera program that start with a "CSCA" prefix except the following courses, which cannot be applied toward MS-DS degree requirements:

• CSCA 5214 Computing, Ethics and Society 1 - Foundations
• CSCA 5224 Computing, Ethics and Society 2 - Algorithmic Bias and Professional Ethics
• CSCA 5234 Computing, Ethics and Society 3 - Applications

You may not apply the three CSCA courses above, EMEA courses other than the six listed above, or any MS-EE courses toward MS-DS degree requirements. 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 CU ��«����Ƶ programs.

No, students are provided with everything they need to succeed within each course on Coursera.

Non-credit

• Non-credit courses are flexible and available on-demand.
• Non-credit courses carry a monthly subscription fee.
• Non-credit completion certificates do not imply the conferral of credit from the ��«����Ƶ or appear on a student’s transcript. 

For-credit

• For-credit courses have session start and end dates. Each session is 8 weeks long.
• For-credit tuition is $525 per credit hour.
• Additional material and assessments must be completed to earn credit; these materials are only available to students who pay tuition. 
• Students receive academic credit on a transcript from the ��«����Ƶ.

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.

Enrolled CU Students (On-campus & Coursera)

• Students currently enrolled in a for-credit MS-DS course can join CU on Coursera without a subscription;

Non-CU Students

• You will need to subscribe to Coursera Plus. You can review more details and purchase a subscription at the .

To enroll in the non-credit versions of courses, sign up for a account, find the courses you are interested in enrolling in, and 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.

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

• Click the Enroll Now button during an open enrollment period
• Pay your tuition 

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

• You will receive two emails from CU ��«����Ƶ: one confirming your enrollment and one with information about your new CU ��«����Ƶ 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 CU ��«����Ƶ account using your IdentiKey.
• Prior to accessing for-credit MS-DS 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. 
• Previously completed assignments will be automatically applied to your for-credit experience. 
• Complete all coursework by the end of the 8-week session to earn CU credit 

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 ��«����Ƶ.

Yes, 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.

After you upgrade, you will complete a final project or exam to earn credit for the course.

You can upgrade from non-credit to for-credit at any time during your learning journey. 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 $525 per credit hour tuition fee. Please note that if you started 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 ��«����Ƶ.

Yes, students can earn a from Coursera for non-credit courses and specializations. This non-credit certificate of completion does not earn transcripted credit from the ��«����Ƶ, 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 CU ��«����Ƶ tuition.

The cost of the Master of Science in Data Science is $525 per credit hour. The program requires 30 credit hours of coursework.

You do not need a Coursera subscription to enroll in a for-credit course when you pay CU ��«����Ƶ tuition.

Are you a current CU student, faculty, or staff member?

• You may enroll in individual, non-credit courses or specializations without a subscription;

Non-CU Students

• You will need to subscribe to Coursera Plus. You can review more details and purchase a subscription at the .
• If you decide to later upgrade to a for-credit version, you will also have paid , along with the associated tuition.

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

We accept the following forms of payment: 

• Pay online from a U.S. checking or savings account (no fee). If a payment is returned for insufficient funds, a $20 returned payment fee is charged.
• Pay online with a U.S. credit or debit card with a service fee of 2.75% for each transaction.
• Pay online with a wire transfer via Flywire.

• U.S. federal student aid: This program is not currently eligible for financial aid provided through the Free Application for Federal Student Aid (FAFSA).
• Scholarships: CU ��«����Ƶ does not currently offer scholarships for this program. However, you can search for private scholarships and improve your chances of success with our tips to apply. 
• Student loans: Private loans may be an option for you. Contact the Office of Financial Aid if you have questions. Note that enrollment in this program will not affect your existing federal student loans (i.e., you will not be able to defer your loans based on half-time or full-time enrollment status).
• Employer tuition assistance: Many employers value the skills this program provides. Check directly with your employer to see if they have a "tuition assistance" or "tuition reimbursement" program, where your employer helps pay your tuition. 
• Tax benefits: Consult a tax advisor to determine which credits and deductions might apply to you. Learn more about .

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

No. When you pay CU ��«����Ƶ 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 you are within 14 days from the class start date or enrollment date (whichever is later), and you must not have accessed restricted content in the course. A refund will be returned to your credit card within 7-10 business days. When a course is dropped under these conditions, it will not appear on your student record. Visit the Office of the Registrar for more information.

No, exam proctoring costs are included in your CU ��«����Ƶ tuition.

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

MS-DS 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. 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, 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, the Quinncia online resume review service, and the Forever Buffs alumni association.

Yes, check with your VA advisor and visit the  for more information.

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

Online MS-DS students do not have access to campus facilities but can access online resources including CU ��«����Ƶ libraries, Career Services, and ForeverBuffs Alumni Services.

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

Yes, students taking for-credit classes receive an official @colorado.edu email address.

Yes, students taking for-credit classes receive an IdentiKey, which includes your CU ��«����Ƶ login name and password. Your IdentiKey uniquely identifies you and acts as your student identification number. Students can also receive a physical Buff OneCard (student ID card) for $30 by emailing a headshot, photo ID, and mailing address to boc@colorado.edu from your colorado.edu student email address. Learn more on the Buff OneCard site.

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

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), Linus 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. There are currently no internships available.

Students who have been admitted into the degree program will have lifelong access to Handshake through CU ��«����Ƶ 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 ��«����Ƶ graduate, you will join the alumni association, Forever Buffs. 

Graduates from CU ��«����Ƶ go on to work at top companies including Amazon, Apple, Boeing, Disney, Google, IBM, Lockheed Martin, NASA, NBC, Twitter, and Yelp.

Recent graduates from MS-DS have gone on to work in the following roles:

• Data Scientist II
• System Development Engineer I 
• Analyst
• Associate Data Scientist
• Supply Chain Insights Analyst
• Adjunct Faculty in Introduction to Statistics
• Associate Scientist in Computational Science
• Software Developer II
• Data Modeler
• Data Analyst III
• Full Stack Developer

Recent graduates from MS-DS have gone on to work at the following companies:

• Intuit
• Niagara Bottling
• Civitas Resources
• Xcel Energy
• Cummins Inc.
• Metropolitan State University of Denver
• Cogent BioScience
• Dish Networks
• Kroenke Sport & Entertainment
• Imperial Health Plan of California, Inc.
• American Express

*The job information mentioned above pertains to positions secured in proximity to or shortly after a student's graduation in May 2023.

The median annual salary for data scientists is $100,560, according to the . This is nearly twice as high as the average median salary in the United States.

Prospective students can email us at datascience@colorado.edu. Current students can reach us at msds-support@colorado.edu.

If you are having difficulties with your final exams, please email us at msds-support@colorado.edu.