The MS-DS on Coursera does not have an application. That means no transcripts, tests, or application fees! Simply prove you can do the work and you are in.

Prerequisite Knowledge

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

  • 笔测迟丑辞苍听
  • R programming听
  • Calculus including derivatives and integrals
  • Linear algebra including matrix multiplication, matrix inversion, and solving linear systems using matrices
  • Statistics

If you would like to brush up on the above skills before starting the program, consider the following classes听on Coursera:

  • 颁补濒肠耻濒耻蝉:听
  • Linear Algebra:
  • R Programming:听
  • Python:听
  • Statistics:听

Not sure if you are ready? Try 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.

Admission Requirements

Simply complete a pathway specialization to demonstrate your proficiency and be admitted to the program. 乐播传媒 are automatically admitted to the degree program after meeting all admission requirements below.听All admitted students receive an official offer letter via email. See the MS-DS on Coursera Student Handbook for details.

  • Pass听one pathway with a pathway GPA of 3.0 or higher听
  • Earn a C or better in all pathway courses within your chosen pathway
  • Earn听an overall cumulative GPA of 3.0 or higher听
  • Indicate interest听in degree admission (via the enrollment form)

A pathway specialization听(or "pathway") is a series of three 1-credit courses with a focus on either statistics or computer science. The credits you earn for pathway courses are part of the required听curriculum, so you make direct progress toward your degree as you complete your pathway. Choose one of the following pathways:

Statistics Pathway
Data Science Foundations: Statistical Inference

  • DTSA 5001: 鈥婸robability Theory: Applications for Data Science
  • DTSA 5002: Statistical Inference for Estimation in Data Science
  • DTSA 5003: Hypothesis Testing for Data Science

Computer Science Pathway
Data Science Foundations: Data Structures and Algorithms

  • DTSA 5501: Algorithms for Searching, Sorting & Indexing
  • DTSA 5502: Trees & Graphs: Basics
  • DTSA 5503: Dynamic Programming, Greedy Algorithms

Converting Grades

Converting Percentage (%) to Letter Grade (A鈥揊)

You can find the grading breakdown for each course on Coursera.听Simply go to the course in question, find the听Reading: Syllabus听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鈥揊) to the 4.0 Scale

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

Getting Started

To get started, select and enroll in a pathway, pay your tuition, and complete your pathway with a 3.0 GPA or better to be admitted to the program.听

  • Click during any open enrollment period听
  • Complete the registration form for 1鈥�3 courses in your chosen pathway
  • Pay your tuition
  • Check your email for the next steps
  • Complete your onboarding course
  • Complete your pathway courses by the last day of the term

Once you have enrolled in a pathway and paid your tuition, you will receive two emails from CU Boulder: one confirming your enrollment and one with information about your new CU Boulder 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 Boulder account using your IdentiKey.听