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Graduate Degree

Master of Science in Data Science

On-campus, face-to-face Master of Science in Data Science (MSDS)
Degree Options:
  • Master of Science in Data Science (MSDS)

The demand for data scientists, data engineers, and data architects is rapidly growing across many industries. According to the U.S. Bureau of Labor Statistics, employment of data scientists is projected to grow 35% from 2022 to 2032, which is much faster than the average for all occupations.

Why Pursue a Master's Degree in Data Science?

Variety of career opportunities. Data science is a broad field that encompasses many different roles and industries. With a data science degree, you can work in fields as diverse as finance, healthcare, marketing, government, and technology because the valuable analytical and problem-solving skills you will learn can be applied to a wide range of industries and professions.

High earning potential. Data science is a high-paying field, and earning a data science degree can help you command a higher salary. According to Glassdoor, the average base salary for a data scientist in the U.S. is around $117,000 per year.

Meaningful and challenging work. Many data scientists find their work to be intellectually challenging and rewarding as they are able to use data to solve real-world problems and make a tangible impact on their organizations and communities.

TLU's program is on campus. For some students, an in-person program is preferred over a 100% online program. TLU's MSDS is on campus so students receive one-on-one instruction with tenured professors who hold doctorate degrees in mathematics, applied mathematics/engineering mechanics, and electrical and computer engineering from The University of Texas at Austin and the University of Missouri-Kansas City.

Earning a Master's Degree in Data Science is a smart career move for anyone who wants to enter and advance in this rapidly growing and rewarding field.

Admissions Requirements & How to Apply

  • Applicants must already hold a bachelor’s degree from an accredited university.
  • Complete and submit the TLU Application for Admission at (select Graduate Applications).
  • Submit all official transcripts from all colleges and universities attended.
  • Submit letter providing additional information to be considered by the admissions committee (optional).
  • Applicants must have successfully completed the following undergraduate coursework, or their equivalents, to be considered for admission:
    • ISYS 232: Business Spreadsheet Applications
    • CSCI 248: Object-Oriented Programming or equivalent
    • MATH 136: Business Calculus or both MATH 241 and MATH 242
    • STAT 374: Statistics
  • Current TLU students may apply to the program as concurrent students. Please contact Elliott Powell, Director of Transfer and Graduate Admissions for information on how to apply.

Apply Now to Earn Your MSDS

          Application Deadlines & Program Details

          Fall Application:

          March 1 - Early Deadline

          May 1 - Priority Deadline

          July 1 - Late Deadline

          Spring Application:

          Oct. 1 - Early Deadline

          Nov. 1 - Priority Deadline

          Dec. 1 - Late Deadline

          Apply Now to Earn Your MSDS

          Program Details:

          • All classes are face-to-face at TLU's Seguin campus
          • 30-credit hour program / 10 courses total
          • Fall and Spring starts

            Program Costs:

            • Tuition is based on a block rate (12-18 hours) with a graduate scholarship for admitted students. Students should contact Student Financial Services for questions related to tuition.
            • $420 per year student services fee
            • $200 per year technology fee
            • $400 enrollment deposit applied to tuition. No application fee
            • Books are not included in tuition and fees

            Curriculum Overview

            Core Curriculum (15 hours):

            • DASC 531 - Data Analysis with R
            • DASC 532 - Data Mining
            • DASC 533 - Visualization and Communication
            • DASC 534 - Advanced Statistical Methods I
            • DASC 535 - Advanced Statistical Methods II

            Data Science Tools (9 hours):

            • DASC 536 - Bayesian Statistics
            • DASC 537 - Mathematical Statistics
            • DASC 538 - Computational Methods & Approximations
            • DASC 570 - Database Design
            • DASC 571 - Cyber Security
            • DASC 572 - Advanced Data Mining and Machine Learning

            Data Science Applications (6 hours)

            • DASC 573 - Data Science in Action
            • DASC 539 - Data Science Internship or DASC 599 - Thesis
              Contact Us

              Elliott Powell

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