Overview

The Master of Science in Data Science (M.Sc.) at the University of Texas at Austin is a comprehensive programme that prepares graduates for a career in one of the most dynamic fields today. As the demand for data scientists continues to surge across various sectors such as academia, government, healthcare, and non-profit organisations, this programme equips students with the critical skills needed to excel in this competitive landscape. The MSDS programme is a collaborative effort between the Department of Statistics and Data Sciences and the Department of Computer Science, ensuring a robust educational experience that integrates both statistical and computational methodologies.

Why Data Science at the University of Texas at Austin?

UT Austin is recognised as a top-ranked public university, renowned for its academic excellence and innovative research. The MSDS programme benefits from strong partnerships within the industry, providing students with access to cutting-edge facilities and resources. The curriculum is designed to offer a comprehensive understanding of data science, ensuring that graduates are well-prepared to tackle complex data challenges. With a focus on affordability, the programme offers an advanced degree at competitive tuition rates, making it an attractive option for aspiring data scientists.

Tuition Fee Breakdown

The tuition fees for the Master of Science in Data Science are structured as follows:

International Students: USD 9,081 per semester
Domestic Students: USD 9,081 per semester
Local Students: USD 4,608 per semester

Visit the Fees and Funding section for a breakdown in your local currency.

Syllabus

The curriculum comprises ten courses, including three foundational courses and seven additional required or elective courses. The foundational courses are:

Data Structures & Algorithms
Probability & Inference
Regression & Predictive Modeling

Students will also engage in advanced topics such as:

Deep Learning
Machine Learning
Data Exploration & Visualization
Natural Language Processing
Reinforcement Learning

This diverse syllabus ensures that students gain a well-rounded education in data science, preparing them for various roles in the industry.

Careers with Data Science

Graduates of the MSDS programme are well-positioned to enter a variety of industries, leveraging their skills in data analysis, machine learning, and computational methods. Alumni have found successful careers in sectors such as technology, finance, healthcare, and government, often taking on roles such as data analysts, data scientists, and machine learning engineers. The programme's strong emphasis on practical skills and real-world applications ensures that graduates are equipped to meet the evolving demands of the job market.

Programme Structure

Courses include:

Advanced Predictive Models for Complex Data
Design and Causal Inference for Data-Based Decision Making
Data Exploration, Visualization, and Foundations of Unsupervised Learning
Principles of Machine Learning
Deep Learning
Natural Language Processing
Optimization

Key information

Start dates & application deadlines

Starting 2027-01-11 00:00:00
- Apply before 2026-09-01 00:00:00
Starting 2027-08-24 00:00:00
- Apply before 2027-04-01 00:00:00

Language

English

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IELTS

6.5

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Credits

30 SCH

Delivered

Online

Campus Location

Austin, United States

Disciplines

Data Science & Big Data View 197 other Masters in Data Science & Big Data in United States

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Academic requirements

GPA

English requirements

TOEFL^® IBT

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IELTS

6.5

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Other requirements

General requirements

Statement of Purpose: Candidates should limit their submission to two pages describing their reasons for pursuing graduate study, academic and professional interests and goals. It may also include events/experiences that prepared you for graduate study.
CV/Resume: At the end of the CV/resume please include a section about how you have covered relevant coursework (via MOOC’s, courses, work) and the grade associated with this course (assuming it was through a college or university).
Mathematics & Programming Preparation Form: Applicants must provide relevant information regarding coursework taken in the subject areas of linear algebra, multivariate calculus, introductory statistics, and programming. This form must be uploaded as a “Mathematics Preparation Form” document through the Document Upload System on the applicant’s MyStatus Portal.
TOEFL or IELTS.
Transcripts.

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.

International Applies to you

Applies to you

Non-residents

18162 USD / year

≈ 18162 USD / year
Out-of-State

18162 USD / year

≈ 18162 USD / year
Domestic

Applies to you

In-State

9216 USD / year

≈ 9216 USD / year

Funding

Win a €10000 Scholarship! Deadline: 30 June 2020

Embark on your journey with the Studyportals Scholarship! We're giving away a total of 20,000 euros to help you achieve your dream of studying abroad.

Win a €10000 Scholarship! Deadline: 30 June 2020

Embark on your journey with the Studyportals Scholarship! We're giving away a total of 20,000 euros to help you achieve your dream of studying abroad.

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Scholarships Information

Below you will find Master's scholarship opportunities for Data Science.

Available Scholarships

You are eligible to apply for these scholarships but a selection process will still be applied by the provider.

On this page

About

Overview

Programme Structure

Key information

Start dates & application deadlines

Language

Prepare for Your English Test

Credits

Delivered

Campus Location

Disciplines

What students do after studying

Academic requirements

English requirements

Prepare for Your English Test

Other requirements

General requirements

Tuition Fees

International Applies to you

Domestic

Funding

Scholarships Information

Available Scholarships

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