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Master’s Degree in Data Science from The University of Texas at Austin

Data science and analytics is a booming field with various applications across industries, from information technology to business analytics to artificial intelligence. Be prepared for the fastest growing, highest demanded job prospect in recent history before you have work experience.

About the program

  • In demand skills for a growing market: Data science and analytics is a booming field with various applications across industries, from information technology to business analytics to artificial intelligence. This program ensures that graduates have the skillset to be competitive candidates in the job market as data scientists.
  • Top-ranked for Innovation: University of Texas at Austin is ranked as the #10 Most Innovative Public School. U.S. News & World Report, 2021.
  • Multidisciplinary learning: The University of Texas at Austin's Department of Statistics and Data Sciences has partnered with the Department of Computer Science to offer a Master of Science in Data Science online. This new online master's degree program embodies the defining principles of data science, combining the leaders from both fields to present a curriculum designed from the ground up.

The degree program for data science offers foundational knowledge in statistical theory while preparing students to apply their skills in the computer science realm for wide industry applications. With a curriculum that includes courses such as simulation, data visualization, machine learning, and optimization, students can expect a rigorous curriculum that combines ideas and methods from both a statistical and computer science perspective.

Our data science program is designed to prepare you for the fastest growing, highest demanded job prospect in recent history before you have work experience. Step into the world of data-driven models and multi-dimensional datasets. Use computer programming and applied data science to find answers in the areas of bioinformatics, linguistics, industry, academia, government, healthcare, and nonprofits to name just a few.

About The University of Texas at Austin

Educating students, providing care for patients, conducting groundbreaking research, and serving the needs of Texans and the nation for more than 130 years, The University of Texas System is one of the largest public university systems in the United States, with nine academic universities and six health science centers. Student enrollment exceeded 215,000 in the 2013 academic year. The U. T. System confers more than one-third of the state’s undergraduate degrees and educates nearly three-fourths of the state’s health care professionals annually. The U. T. System has an annual operating budget of $13.9 billion (FY 2013) including $2.5 billion in sponsored programs funded by federal, state, local and private sources. With 89,000 employees, the U. T. System is one of the largest employers in the state.

As the flagship campus of the U. T. System, The University of Texas at Austin is offering a number of showcase courses from some of our most accomplished faculty. 

At The University of Texas at Austin, we say: “What starts here changes the world.” Be that change with enrollment in the online master's degree program. Prepare yourself for a career in the data science field with high-quality, flexible online courses.

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Curriculum

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

DSC 381: Probability and Simulation Based Inference for Data Science

DSC 382: Foundations of Regression and Predictive Modeling

DSC 395T: Data Structures & Algorithms

Non-core requirements include the following courses:

  • DSC 383: Advanced Predictive Models for Complex Data (Pre-requisite of DSC 382)
  • DSC 384: Design Principles and Causal Inference for Data-Based Decision Making (No Pre-requisite)
  • DSC 385: Data Exploration, Visualization, and Foundations of Unsupervised Learning (No Prerequisite)
  • DSC 91L: Principles of Machine Learning (Pre-requisite of DSC 382)
  • DSC 395T: Natural Language Processing (No Prerequisite)
  • DSC 395T: Optimization (Pre-requisite of DSC 388G)
  • DSC 395T: Deep Learning (Pre-requisite of DSC 382)
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Application requirements

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.


A typical MSDS applicant will:

  • Have a regionally accredited bachelor’s degree in: statistics, computer science, computer engineering, mathematics, electrical engineering, or similar.

  • Competitive applicants have a cumulative GPA of 3.0 or higher.


An atypical MSDS candidate will:

  • Have a regionally accredited bachelor’s degree in an unrelated field (a field not listed above).

  • Need to use their CV and personal statement to convey their passion for data science and demonstrate their functional use of data science through work experience

  • Need to have certain coursework prior to enrolling in the program: - Math (Calculus and linear algebra), including: Multivariable Calculus (eg. MATH 408D) and Linear Algebra (eg. MATH 341 or equivalent) - Statistics (College level introduction to statistics), including: Introduction to Statistics (eg. SDS 302, 304, 306 or equivalents) and Biostatistics (eg. SDS 328M or equivalents) - Some experience in at least one of the following programming languages: 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.


Admissions take into consideration the following application materials:

  • Bachelor’s degree (see prerequisites)

  • CV/Resume

  • Statement of Purpose

  • Transcripts from all universities attended

  • Preparedness in Mathematics & Programming Preparation Form*

  • Quest Assessment

  • TOEFL or IELTS - Required for International Students***

  • GRE scores - Currently Optional**

  • Letter(s) of recommendation (optional)


Since it is a twofold process to apply to UT Austin’s MSDS program, we strongly recommend that applicants complete their application before the priority deadline to allow for their required materials to be received and processed by the final deadline.

All materials are due no later than the final application deadline. Please submit the “Request Info” form above to receive additional information on the MSDS program as a whole including detailed resources for your application materials and the admissions process.


*Applicants must provide relevant information regarding coursework taken in the subject areas of linear algebra, multivariate calculus, introductory statistics, and programming. The Mathematics & Programming Preparation Form can be found in the Application Materials section of the Admissions & Application tab of the MSDS website.


**GRE Score: Submitting GRE scores is optional for admittance consideration for all applicants. Please keep in mind:

  • We encourage all applicants to submit your official GRE scores in an effort to bolster your application.

  • If you do not have a relevant or related degree (as clarified above), or have not been in school for over 10 years, a GRE score will assist the Admissions Committee in their review.


**TOEFL or IELTS: The minimum scores considered acceptable for admission by the Graduate School are:

  • TOEFL: 79 on the Internet-based test (iBT)

  • IELTS: An overall band of 6.5 on the Academic Examination


Application Deadlines for August 2024

Priority Application Deadline

April 1, 2024

Final Application Deadline

May 1, 2024

*All application materials are due no later than the final deadline.


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