The University of Kentucky Master of Science in Data Science is a campus program in Lexington that combines computer science, biostatistics, and biomedical informatics. Students complete core work in data science and statistical modeling, choose a concentration, and finish an applied project. The curriculum has a clear machine learning connection through courses in machine learning, artificial intelligence, data mining, neural networks, computer vision, and large-scale data science.
Quick Facts
| Category | Details |
|---|---|
| School | University of Kentucky |
| Location | Lexington, Kentucky |
| Degree | MS in Data Science |
| Credits | 33 credits |
| Format | Campus |
| Estimated tuition | $27,769.50 resident; $69,316.50 nonresident |
| Estimated length | About 2 years full time |
| Concentrations | Biomedical Informatics; Software and Systems |
Curriculum
The 33-credit curriculum combines a 27-credit major with a 6-credit concentration. The 15-credit major core includes Fundamentals of Data Science, Introduction to Biostatistical Methods, Linear Regression, three semesters of Research Seminar in Data Science, and the Master’s Project in Data Science.
Students also complete one 3-credit guided computer science elective and 9 credits of approved free electives. At least two free-elective courses must have a strong data science component and be at the 600 or 700 level. Relevant options include:
- CS 460G: Machine Learning
- CS 463G: Introduction to Artificial Intelligence
- CS 626: Large Scale Data Science
- CS 628: Data Mining
- CS 636: Computer Vision
- CS 688: Neural Networks
- BMI 733: Biomedical Natural Language Processing
Concentrations
The Biomedical Informatics concentration requires Introduction to Bioinformatics plus one course in clinical informatics, biomedical natural language processing, or biomedical image analysis. This option suits students who want to apply data science to healthcare, clinical records, genomics, or medical imaging.
The Software and Systems concentration requires two courses selected from machine learning or data mining, large-scale data science, and intermediate database topics. This option provides the clearest path for students focused on machine learning engineering, scalable systems, or data infrastructure.
Credits and Program Length
The degree requires 33 credits. UK does not publish a fixed completion schedule on the program pages. Students should plan for about two years of full-time study, although course sequencing, elective availability, and the capstone project can affect the timeline. This duration is an estimate rather than a university guarantee.
Tuition and Cost
UK lists 2026–27 standard campus graduate rates of $841.50 per credit for Kentucky residents and $2,100.50 per credit for nonresidents. Multiplying those rates by 33 credits produces estimated tuition of $27,769.50 for residents and $69,316.50 for nonresidents.
The published per-credit rates include mandatory fees. These estimates do not include housing, books, transportation, health insurance, or future tuition increases. Full-time students pay semester rates, so a student’s actual total can vary with course load and billing rules. Admitted degree students may also pursue assistantships and fellowships through the Graduate School and academic departments.
Admissions
Applicants use the UK Graduate School online application. The Graduate School requires a bachelor’s degree from an accredited U.S. institution or a recognized international institution, a minimum undergraduate GPA of 2.75, and a minimum 3.0 GPA on prior graduate work. International applicants must also meet English proficiency requirements.
The university directs applicants to check the data science program page for any program-specific documents or earlier deadlines. The program page lists fall and spring entry. Applicants should verify the current deadline before submitting because dates change by admission cycle and international deadlines occur earlier.
Machine Learning and AI Focus
The program has a meaningful machine learning and AI focus, but it remains a broad data science degree. Every student selects at least one guided computer science course, and the Software and Systems concentration can include machine learning or data mining. Free electives can extend the technical focus through artificial intelligence, neural networks, computer vision, natural language processing, and large-scale data science.
Students who want the strongest machine learning path should choose the Software and Systems concentration and use free electives for advanced AI courses. Students interested in health data can combine the Biomedical Informatics concentration with natural language processing or image analysis.
Capstone Project
Each student completes a supervised data science project and written report. The student forms an advisory committee, schedules a master’s examination, and presents and defends the project. This requirement gives students a substantial applied or research-based project for a portfolio, but it also requires early planning with a faculty supervisor.
Who Is This Program Best For?
UK’s MS in Data Science is a strong fit for students who want an interdisciplinary campus program with options in computing or biomedical applications. It is especially useful for Kentucky residents because the resident tuition estimate is far below the nonresident estimate. Students who need a fully online program or a fixed accelerated schedule should compare other options.
Bottom Line
The University of Kentucky offers a solid 33-credit data science degree with required statistics, flexible electives, two concentration choices, and a defended capstone project. Its AI and machine learning depth depends partly on course selection, but students can build a focused technical plan through the Software and Systems concentration and advanced electives. The main drawback is the high nonresident tuition rate.
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