The University of Michigan offers a Master of Science in Data Science on its Ann Arbor campus. The degree is run jointly by the Department of Statistics, the Computer Science and Engineering Division, the School of Information, and the Department of Biostatistics.
The program is taught in person and has no tracks. Every student takes one machine learning or data mining course, chosen from a list of nine. Further machine learning, computer vision, natural language processing, and artificial intelligence courses are available as electives.
Last reviewed: October 2026
Quick Facts
| Degree | MS in Data Science |
| Tracks | None |
| School | Department of Statistics (College of Literature, Science, and the Arts), with Computer Science and Engineering, the School of Information, and Biostatistics |
| Location | Ann Arbor, Michigan |
| Format | Campus |
| Credits | About 42 to 48 without course waivers; at least 25 in residence |
| Culminating Experience | Capstone course or approved project, no thesis |
| Minimum GPA | No formal minimum |
| GRE | Not required |
| Application Deadline | January 15 (fall entry only) |
| Typical Length | 2 years (4 semesters) |
| STEM Designated | Yes |
Official MS in Data Science page
Curriculum
The Ann Arbor campus does not offer a standalone master’s degree in machine learning. The MS in Data Science is designed to give every student balanced training in statistical and computational skills, and the program has chosen not to offer sub-plans or tracks.
The university does not publish a single credit total. The program guide lists credits by requirement area:
- 17 to 19 credits of pre-core courses
- 7 to 8 credits in data management and manipulation
- 6 to 8 credits in data science techniques
- 3 to 4 credits of capstone
- At least 9 credits of electives
That comes to about 42 to 48 credits for a student with no waivers. Admitted students can ask to waive pre-core, data management, and data science techniques courses they have already passed elsewhere with a B- or better. At least 25 graduate credits must be completed in the program, 18 of them at the advanced graduate level.
Pre-Core Courses
- MATH/DATASCI 403 – Introduction to Discrete Mathematics
- EECS 402 – Programming for Scientists and Engineers
- EECS 403 – Graduate Foundations of Data Structures and Algorithms
- One probability course: BIOSTAT 601 – Probability and Distribution Theory, MATH/STATS 425 – Introduction to Probability, or STATS 510 – Probability and Distribution
- One inference course: BIOSTAT 602 – Biostatistical Inference, STATS 426 – Introduction to Theoretical Statistics, or STATS 511 – Statistical Inference
Data Management and Manipulation
Students take one database course:
- EECS 484 – Database Management Systems
- CSE 584 – Advanced Database Systems
They also take one of the following:
- EECS 485 – Web Systems
- EECS 486 – Information Retrieval and Web Search
- CSE 549/SI 650 – Information Retrieval
- SI 618 – Data Manipulation and Analysis
- DATASCI 507 – Data Science and Analytics using Python
Data Science Techniques
Students take one regression course:
- BIOSTAT 650 – Applied Statistics I: Linear Regression
- STATS 413 – Applied Regression Analysis
- STATS 500 – Statistical Learning I: Regression
They also take one machine learning or data mining course:
- DATASCI 415 – Data Mining and Statistical Learning
- DATASCI 503 – Statistical Machine Learning
- EECS 545 – Machine Learning (CSE)
- EECS 553 – Machine Learning (ECE)
- EECS 476 – Data Mining
- CSE 576 – Advanced Data Mining
- SI 670 – Applied Machine Learning
- SI 671 – Data Mining: Methods and Applications
- BIOSTAT 626 – Machine Learning for Health Sciences
Because this is a one-course requirement, a student can satisfy it with a data mining course and graduate without a course titled machine learning. Students who want more depth use their electives.
Electives
Students take at least one course of 3 or more credits from each of three categories: Principles of Data Science, Data Analysis, and Computation. At least two electives must be advanced graduate courses. Each course can count toward only one requirement.
Electives of interest to machine learning students include:
- ECE 551 – Matrix Methods for Signal Processing, Data Analysis, and Machine Learning
- ECE 556 – Image Processing
- ECE 559 – Optimization Methods for SIPML
- EECS 504 – Foundations of Computer Vision
- EECS 542 – Advanced Topics in Computer Vision
- CSE 592 – Artificial Intelligence
- CSE 595/SI 561 – Natural Language Processing
- SI 630 – Natural Language Processing: Algorithms and People
- STATS 601 – Advanced Statistical Learning
- DATASCI 551 – Bayesian Modeling and Computation
- BIOSTAT 625 – Computing with Big Data
- CSE 587 – Parallel Computing
Capstone
Students complete the capstone through one approved course:
- STATS 504 – Practice and Communication in Applied Statistics
- SI 699 – Big Data Analytics
- BIOSTAT 699 – Analysis of Biostatistical Investigations
With a pre-approved proposal, students can instead complete a research project with a University of Michigan faculty member, or a project through the Multidisciplinary Design Program. The program has no thesis option, and an internship is not required.
Cost and Tuition
The University of Michigan charges full-time graduate students a flat rate per term, with separate rates for Michigan residents and nonresidents. International students pay the nonresident rate.
For the 2026–27 academic year, the university’s tuition and fees schedule lists these full-time rates for graduate students in the College of Literature, Science, and the Arts:
| Category | Michigan Resident | Nonresident |
|---|---|---|
| Tuition and required fees, per term | $15,900 | $31,802 |
| Tuition and required fees, fall and winter | $31,800 | $63,604 |
These figures already include required fees, among them a $185 infrastructure maintenance fee, a $233.24 health service fee, and an $80 registration fee. Students with F or J visa status also pay a $500 International Fee each term.
Over the four semesters most students need, tuition and required fees come to about $63,600 for a Michigan resident and about $127,208 for a nonresident. The program states that the cost of the degree is the student’s responsibility.
Rates for part-time enrollment are set by the Office of the Registrar and are not shown here. Rates can change each year, so students should confirm current costs with the Registrar.
View University of Michigan cost of attendance estimates
Admission Requirements
The program has no formal minimum GPA. Applications are reviewed holistically, and grades in relevant courses count for more than the overall GPA.
An undergraduate major in data science is not required. Applicants are expected to have completed:
- two semesters of college calculus
- one semester of linear or matrix algebra
- one introduction to computing course
These must be college courses from an accredited institution that issues a grade and transcript. Massive open online courses are not accepted. The program notes that most successful applicants hold a degree in data science, computer science, information, engineering, physics, statistics, or mathematics.
Application Materials
Applicants submit:
- online application and application fee ($75 for U.S. citizens and permanent residents, $90 for international applicants)
- prerequisite information, with a syllabus for each prerequisite course
- transcripts
- two letters of recommendation
- statement of purpose
- personal statement of up to 500 words
- resume or CV
- proof of English proficiency when required
The GRE is not required. Applicants who have taken it may submit scores as additional information. The minimum TOEFL score is 84 on the internet-based test, and Duolingo is not accepted.
Application Deadlines
| Entry Term | Deadline |
|---|---|
| Fall | January 15 |
The program admits students for fall only. Applications and all supporting materials are due by 11:59 p.m. Pacific Time on January 15. There is no priority deadline and no rolling review, and decisions are typically made in March or April.
Program Format
The MS in Data Science is an in-person program on the Ann Arbor campus. It is not offered online.
Most students finish in two years, or four semesters. The program recommends taking no more than three or four courses each semester.
Part-time enrollment is possible with a course plan agreed with the program advisor, but it is typically not available to international students on F-1 visas. Only some classes meet in the evening, so the degree cannot be completed through evening courses alone.
The degree is recognized as a STEM program, and graduates are eligible for the STEM OPT extension. Coursework uses R, Python, and C++.
Students already enrolled in another graduate program at the Ann Arbor campus can add the MS in Data Science as a dual degree.
Who Is This Program Best For?
The University of Michigan MS in Data Science is a strong option for students who want statistics and computing in equal measure, taught in person across four academic units.
It may be especially appealing to students interested in:
- machine learning and data mining on a statistics foundation
- databases, information retrieval, and data manipulation
- computer vision and natural language processing as electives
- probability, inference, and regression
- entering data science from a mathematics, physics, or engineering major
- a STEM-designated degree with no GRE requirement
The degree is a data science master’s first. Only one machine learning or data mining course is required, and deep learning, computer vision, and natural language processing are electives. The program is long for a master’s degree, admits for fall only, has no online or thesis option, and nonresident costs are high. Students who want a degree built entirely around machine learning or AI, a shorter program, or online study may want to compare other Michigan schools or the university’s online Master of Applied Data Science.
Official University of Michigan Program Links
- MS in Data Science program page
- MDS Program Guide (PDF)
- MDS capstone guidelines
- Data Science master’s application
- FAQs for prospective students
- Computer Science and Engineering page for the degree
- 2026–27 tuition and fees schedule (PDF)
- Cost of attendance estimates
Related Machine Learning Programs in Michigan
Students can also compare University of Michigan with other master’s programs in machine learning, artificial intelligence, and related fields offered in Michigan.
- Eastern Michigan University – Ypsilanti
- Grand Valley State University – Grand Rapids
- Lawrence Technological University – Southfield
- Michigan State University – East Lansing
- Michigan Technological University – Houghton
- Oakland University – Rochester
- University of Michigan-Dearborn – Dearborn
- Wayne State University – Detroit
- Western Michigan University – Kalamazoo