The University of Texas at Arlington’s MS in Data Science is a 30-credit engineering degree offered online and on campus. Students study computing, probability, statistics, machine learning, visualization, and big data management.
UTA states that students can complete the program in two years. The degree ends with a capstone project or an applied project that may connect with a student’s workplace.
Quick Facts
| School | University of Texas at Arlington |
| Location | Arlington, Texas |
| Degree | Master of Science in Data Science |
| Credits | 30 |
| Format | Online or campus |
| Length | 2 years |
| Estimated tuition and fees | $18,407 for Texas residents; $39,143 for nonresidents |
| Machine learning focus | Required machine learning course plus AI-related electives |
Curriculum
The MSDS degree plan begins with 18 credits of required foundation courses:
| Course | Credits |
|---|---|
| DASC 5300: Foundation of Computing | 3 |
| DASC 5301: Data Science | 3 |
| DASC 5302: Introduction to Probability and Statistics | 3 |
| DASC 5304: Machine Learning | 3 |
| DASC 5305: Data Visualization | 3 |
| DASC 5306: Big Data Management | 3 |
Students then complete nine specialization credits and a three-credit capstone. Approved computer science electives include Artificial Intelligence, Neural Networks, Pattern Recognition, Computer Vision, Data Mining, and Web Data Management.
The degree plan limits students to one Computer Science and Engineering elective. Students who want the strongest AI emphasis should choose that course carefully and confirm current online or campus availability with an advisor.
Capstone or Applied Project
Students finish with DASC 5309: Data Science Capstone Project or DASC 5391: Data Science Applications. The applications option may use an approved internship and a data science project supervised by UTA and the employer.
Credits and Program Length
The degree requires 30 credits. UTA states that it can be completed in two years. The published plan places the six core courses in the first two semesters, followed by specialization courses and the capstone.
Tuition and Cost
UTA lists average 2026-27 graduate tuition and fees of $11,044 for residents and $23,486 for nonresidents for a full-time academic year. Prorating those figures from 18 credits to the 30-credit degree produces planning estimates of approximately $18,407 for Texas residents and $39,143 for nonresidents.
These are estimates rather than university-published program totals. Actual charges depend on course load, residency, delivery format, and term fees. The mandatory fee schedule also lists a $41-per-credit graduate engineering differential. Students should use UTA’s tuition estimator for a schedule-specific figure.
Admissions
Applicants need a bachelor’s degree, preferably in engineering or mathematics, with one semester of calculus and programming experience. UTA expects a 3.0 GPA across the final two undergraduate years and grades of C or better in programming and applied mathematics foundation work.
The GRE is not required. UTA requires transcripts but does not require or review recommendation letters, a statement of purpose, or other supplemental documents for this program. International applicants must meet the university’s English proficiency requirements.
Machine Learning and AI Focus
Machine learning is one of the six required core courses. Students may use their limited CSE elective for a deeper AI subject such as Artificial Intelligence, Neural Networks, Pattern Recognition, Computer Vision, or Data Mining.
The program also develops skills with Python, R, SQL, Spark, predictive modeling, statistical inference, cloud platforms, data pipelines, and large-scale processing. UTA’s Computer Science and Engineering department supports related teaching and research.
Online or Campus Format
UTA offers the MS in Data Science through online and campus options. Students should confirm course availability before selecting electives because the published degree plan lists when courses are typically offered but does not guarantee that every elective appears in both formats each term.
MS in Data Science vs. MS in Applied Data Science
This profile covers the 30-credit MS in Data Science administered through Computer Science and Engineering. UTA also offers a separate MS in Applied Data Science through the College of Science with several subject-area tracks.
Applicants who want a computing-centered curriculum with a required machine learning course should focus on the engineering MSDS reviewed here. The Applied Data Science program may suit students who want to connect data methods with biology, chemistry, environmental science, physics, psychology, or another subject area.
Who Is This Program Best For?
The program is a strong fit for students who want a structured core across programming, statistics, machine learning, visualization, and big data. It also suits working students because UTA provides an online option and permits an employer-connected applied project.
Students who want several advanced computer science electives may find the one-course CSE limit restrictive. Those students should compare UTA’s MS in Computer Science before applying.
Bottom Line
UT Arlington offers a clear machine-learning fit at a public-university price. The required machine learning course, technical core, AI-related elective choices, and applied capstone make the degree relevant for data scientist, machine learning analyst, data engineer, and analytics roles.
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