Skip to main content

Master’s Degree in Data Science

from The University of Texas at Austin
  • $10,000
  • 10 courses
  • Fully Online
  • 1.5-3 years

Master's Overview


As the world grapples with COVID-19, many students are facing challenges taking the GRE, therefore, GRE scores are not required to apply to the program.

The Department of Statistics and Data Sciences at The University of Texas at Austin has partnered with the Department of Computer Science to offer a Master of Science in Data Science. This new online master's program embodies the defining principles of Data Science, combining the leaders from both fields, to present a curriculum designed from the ground up to offer a solid foundational knowledge in Statistical theory upon which to build a Computer Science application. Course curriculum incorporates ideas and methods such as simulation, data visualization, data mining, data analysis, large scale data-based inquiry for big data, and non-standard design methodologies, along with topics of machine learning, algorithmic techniques, and optimization, to tackle issues that come up with large-scale data such as memory and computational speed.

Our program is designed to prepare you for the fastest growing, highest demanded job prospect in recent history. Step into the world of data-driven models and multi-dimensional datasets. Find answers in the areas of bioinformatics, linguistics, industry, academia, government, and nonprofits to name just a few.

At The University of Texas at Austin, we say: “What starts here changes the world.” Be that change. Prepare yourself for a career in Data Science.

Learn More About the Master’s Degree in Data Science

  • #8
    Best-Value Public Colleges
    Kiplinger, 2018
  • #7
    U.S. Public Colleges
    Business First, 2019
  • #14
    Top Public Schools, National Universities
    U.S. News & World Report, 2020
  • #32
    Best Global Universities
    U.S. News & World Report, 2018



  • Tuition (30 credits at $333 each)

*Students may be eligible for federal financial aid subject to federal aid requirements.

Important dates & deadlines


  • Priority deadline
    September 15, 2020
  • Regular deadline
    October 15, 2020
  • Program Start Date
    January 19th, 2021

Prerequisite coursework

Applicants who do not hold a degree in statistics, computer science, computer engineering, mathematics, electrical engineering or similar, will need to have certain course work prior to enrolling in the program:

  • Math (Calculus and linear algebra)
    • Multivariable Calculus (eg. MATH 408D) and
    • Linear Algebra (eg. MATH 341 or equivalent)
  • Statistics (College level introduction to statistics)
    • Introduction to Statistics (eg. SDS 302, 304, 306 or equivalents)
    • Biostatistics (eg. SDS 328M or equivalents)

Some programming experience in at least one of:

  • R, Python, C++

It is the responsibility of the applicant to be prepared for the program prior to starting and to convey that preparedness in their CV and personal statement.

Application requirements

Admissions take into consideration the following items: undergraduate GPA, a relevant field of study, competitive GRE scores, work experience, a statement of purpose, TOEFL score (if applicable) and letters of recommendation (optional).

A typical candidate will have a regionally accredited bachelor’s degree in statistics, computer science, computer engineering, mathematics, electrical engineering or similar.

An atypical candidate will have a regionally accredited bachelor’s degree in an unrelated field but will have a passion for data science and be able to show their functional use of the topic through work experience. This information will need to be conveyed on an applicant’s CV and in their personal statement.

Our Master of Science in Data Science program will target enrollees who would like to build their technical competency and receive rigorous training in the field of data science. The ideal candidate will have some technical background, but have a driving interest in both computational methods and statistical inference, who are excited to advance their career opportunities within industry, government, academia, and nonprofit organizations.

*Details on the Temporarily Waived GRE Requirement: As the world grapples with COVID-19, many students are facing challenges taking the GRE. The GRE requirement for all applicants has officially been waived for Spring 2021, Fall 2021, and Spring 2022 semesters. You may still submit official GRE scores for consideration to bolster your application, but are not required to do so.

Note: it will take 3-5 business days for the GRE waiver to show up on your application.


This is a 30 hour program (3 credit hours per course). There are 3 core required courses and 7 additional required courses for a total of 10 courses. The core requirement will be satisfied with three foundational courses which will provide students with a broad, foundational understanding of the field and will also establish the basis for some of the prescribed electives. They include:

Learn More About the Master’s Degree in Data Science


  • No applicant will be automatically admitted to the program. All applications will be reviewed by a faculty committee to make certain those admitted have the ability to succeed in the program.
  • There is no minimum GRE test score, however applicants admitted to the DS graduate program usually have high quantitative and verbal GRE scores and a math background that includes study through some discrete math. If you feel that your test scores are not valid indicators of your ability, you should explain your concerns in your statement of purpose.
  • GIAC MyStatus: This is the status check site for the Graduate International Admissions Center (GIAC). GIAC verifies application information, test scores, residency and admissions GPA calculations/equivalencies. If you have questions about the information your MyStatus page, please contact GIAC.
  • All GRE/TOEFL scores, transcripts, CV’s, personal statement and recommendation letters (if submitting), must be submitted by the application deadline.
  • You can apply for both programs but you must fill out two separate applications and upload documents to both systems. You can find information about applying to the traditional master’s program here
  • For GRE and TOEFL scores, the Educational Testing Service (ETS) institution code for UT-Austin is 6882. It is not necessary to use a department code. There is no institutional code for the IELTS examination. For IELTS scores, have an official paper score report sent to the Graduate and International Admissions Center.
  • Yes, the TOEFL or the IELTS is required for international applicants. The minimum TOEFL score considered acceptable for admission by the graduate school is a 79 on the Internet-based test (iBT). For the IELTS, a student must have an overall band of 6.5 on the Academic Examination. International applicants who are from a country where English is the only official language are exempt from this requirement. Additionally, applicants are exempt from the requirement if they possess a bachelor’s degree from a U.S. institution or an institution in a country where English is the only official language. The requirement is not waived for applicants who have earned a master’s – but not a bachelor’s – degree from a similar institution.
  • A foreign credential evaluation is not required. If a transcript is written in a language other than English, a complete and official English translation must be uploaded together with the original transcript.
  • Through the ApplyTexas system, you will be given the opportunity to submit three recommenders and provide contact information. The system will send an email to your recommenders directing them to a website where they may upload their letters. In addition, the MyStatus page of ApplyTexas offers a self-service feature you can use to resend the request email to your recommenders, if necessary. Use it to supply an alternate email address if your recommender’s spam filter blocks the original request or has removed the link. You can also add a new recommender or revise your right-to-view status from “retained” to “waived.”
  • The curriculum will consist of ten courses total or 30 hours. Students will take a combination of foundational coursework and elective options. Through completion of the foundational coursework, students will gain a broad understanding of the field. As courses continue to be added to the program, students will also have significant elective flexibility to pursue a course of study best tailored to their professional aspirations.
  • Master of Science in Data Science (MSDS).
  • Yes, your diploma will read exactly as that of an on-campus graduate.
  • 30 credit hours, which equals 10 courses.
  • The program can be completed in 1.5-3 years and the curriculum is highly flexible.
  • Students must maintain a 3.0 GPA throughout the course of the program. If a student drops below 3.0, he or she will have one semester to bring up the GPA. If the student fails to do this, they will be dismissed from the program.
  • A student may take up to five courses each semester. The online master’s courses are of comparable rigor to the traditional courses. For working professionals we recommend taking one to two courses per long semester.
  • Yes, you can start taking classes in either semester.
  • The program will follow the timeline of the traditional semester. The university calendar can be found here
  • Interaction between instructors and/or TA’s will be available through email, online discussion boards, and virtual office hours.
  • Unfortunately, learners from one or more of the following countries or regions will not be able to register for this program: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this program in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.