Michigan Technological University offers a Master of Science in Data Science through the Department of Data Science in the College of Computing.
The 30-credit program is taught on the Houghton campus. Predictive Modeling is required of every student, and the core also requires one course in machine learning or deep learning. Artificial intelligence, data mining, and natural language processing enter the degree through an elective list. Michigan Tech does not offer a standalone master’s degree in machine learning or artificial intelligence.
Last reviewed: October 2026
Quick Facts
| Degree | MS in Data Science |
| School | Department of Data Science, College of Computing |
| Location | Houghton, Michigan |
| Format | Campus |
| Credits | 30 |
| Culminating Experience | Coursework only, report, or thesis |
| Typical GPA | 3.0 or better among admitted applicants |
| GRE | Not required |
| Recommended Deadlines | January 15 (fall), October 15 (spring) |
| Tuition | $1,645 per credit for residents and nonresidents (2026–27) |
| STEM Designated | Yes |
Official MS in Data Science page
Curriculum
The degree is interdisciplinary. Courses come from computer science, mathematical sciences, business, engineering, and other departments across the university, and students work with an advisor to choose electives that fit their background.
Students complete at least 30 graduate credits consisting of:
- 12 credits of core courses
- At least 6 credits of electives, drawn from two different lists
- Up to 6 credits of foundational courses, for students who need them
- Domain electives or research credits for the remaining credits
At least 18 credits must be at the 5000 or 6000 level.
Core Courses
All students take:
- BA 5200 – Information Systems Management and Data Analytics
- MA 5790 – Predictive Modeling
- UN 5550 – Introduction to Data Science
Students then choose one of the following as the fourth core course:
- CS 4801 – Foundations of Machine Learning
- CS 5841 – Deep Learning
- EE 5841 – Deep Learning
This means every student takes one machine learning or deep learning course, but deep learning itself is a choice within the core.
Electives
Students take at least 6 credits of electives, with at least one course from two of three lists. The Computational list holds most of the machine learning content:
- CS 4321 – Introduction to Algorithms
- CS 4801 – Foundations of Machine Learning
- CS 5321 – Advanced Algorithms
- CS 5811 – Advanced Artificial Intelligence
- CS 5821 – Computational Intelligence – Theory and Application
- CS 5831 – Advanced Data Mining
- CS 5841 – Deep Learning
- CS 5851 – Advanced Natural Language Processing (NLP)
- SAT 5114 – Artificial Intelligence in Healthcare
- SAT 5165 – Introduction to Big Data Analytics
- EET 4501 – Applied Machine Learning
- UN 5390 – Scientific Computing
The Mathematics and Statistics list includes:
- MA 4710 – Regression Analysis
- MA 5701 – Statistical Methods
- MA 5741 – Multivariate Statistical Methods
- MA 5761 – Computational Statistics
- MA 5770 – Bayesian Statistics
- MA 5781 – Time Series Analysis and Forecasting
- MA 5791 – Categorical Data Analysis
The Business and Information Systems list includes BA 5650 – Project Management, BA 5740 – Managing Innovation and Technology, MGT 4600 – Management of Technology and Innovation, and MIS 5000 – Emerging Technologies.
Because one elective must come from a second list, students cannot fill the elective requirement with computing courses alone.
Foundational Courses
Up to 6 credits of 3000 and 4000 level courses in databases, statistical programming, and Python can count toward the degree. Options include CS 3425 – Introduction to Database Systems, MA 3740 – Statistical Programming and Analysis, and SAT 4650 – Introduction to Applied Computing in Python Programming. Students who do not need them use domain electives instead.
Domain Electives
Remaining credits come from approved courses in an application area, chosen with an advisor. The lists cover applied computing, business and economics, chemistry, computer science, electrical and computer engineering, forest resources, geosciences, mathematics, and physics. Courses related to machine learning include:
- SAT 5520 – Machine Learning in Security
- SAT 5141 – Clinical Decision Support and AI Modeling
- BE 5870 – Computer Vision for Microscopic Images
- EE 5521 – Detection & Estimation Theory
- EE 5522 – Digital Image Processing
- EE 5532 – Sensing and Processing for Robotics
- MA 5630 – Numerical Optimization
- PH 5396 – Statistics, Data Mining and Machine Learning in Astronomy
Coursework, Report, and Thesis Options
The coursework option requires 30 credits of coursework. The report option requires at least 24 credits of coursework and 2 to 6 report credits. The thesis option requires at least 20 credits of coursework and 6 to 10 thesis research credits. The report and thesis options are open to students who start in the 2026–27 academic year or later.
Cost and Tuition
Michigan Tech is a public university that charges one graduate tuition rate regardless of residency. Michigan residents, out-of-state students, and international students pay the same rate per credit.
Graduate tuition has two tiers, and the university’s 2026–27 tuition schedule places Data Science in the higher engineering and computer science tier:
| Item | 2026–27 Amount |
|---|---|
| Tuition per credit, Data Science MS | $1,645 |
| Tuition for a 9-credit semester | $14,805 |
| Required fees, fall or spring semester | $139 |
| Online course fee, per credit | $38 |
| International student surcharge, per semester | $250 |
At 30 credits, tuition comes to about $49,350, before fees. The university also estimates about $40 per semester in lab and course fees. New international students pay a one-time $100 enrollment surcharge.
The Graduate School’s general cost table shows the standard rate of $1,448 per credit, which applies to programs outside engineering and computing. Rates can change each year, so students should confirm current costs with the Graduate School.
View Michigan Tech graduate costs
Admission Requirements
Applicants need a bachelor’s degree from an accredited institution. Any major is accepted if it included some coursework in introductory programming and statistics.
Michigan Tech does not state a hard minimum GPA for this program. Admitted applicants typically have an undergraduate GPA of 3.0 or better on a 4.0 scale.
The department expects basic knowledge of:
- statistics and mathematical techniques
- computer programming
- information systems and databases
- communications
Application Materials
Applicants submit:
- online graduate application
- student statement
- transcripts
- two letters of recommendation
- resume or curriculum vitae
- proof of English proficiency when required
The GRE is not required. There is no application fee for domestic applicants, and international applicants pay a $10 processing fee. Official transcripts are not needed to start the application but must be uploaded later.
International applicants need at least a 4.5 overall on the TOEFL or a 6.5 overall on the IELTS. The program recommends a TOEFL score of 5 or an IELTS score of 7.0.
Application Deadlines
Admission decisions are made on a rolling basis. The Graduate School asks applicants to apply at least one semester before they plan to start and lists these recommended dates:
| Entry Term | Recommended Deadline |
|---|---|
| Fall | January 15 |
| Spring | October 15 |
Program Format
The MS in Data Science is offered on campus in Houghton, in Michigan’s Upper Peninsula. Michigan Tech does not list an online version of this degree.
The university does not publish a typical length for the coursework option. At the 9-credit full-time load used in its cost estimates, 30 credits takes four semesters. The program handbook gives students five years to finish.
Some core courses are offered once a year, so students should plan their sequence with an advisor. Up to 3 credits of approved cooperative education can count as a domain elective.
The degree is STEM designated for international students. Current Michigan Tech undergraduates can enter through an accelerated master’s option that counts up to nine bachelor’s credits toward the degree.
Who Is This Program Best For?
Michigan Tech’s MS in Data Science is a strong option for students who want an on-campus, interdisciplinary degree that combines statistics, machine learning, and an applied subject area.
It may be especially appealing to students interested in:
- predictive modeling and applied statistics
- machine learning and deep learning
- data mining and natural language processing as electives
- applying data science to health informatics, security, geosciences, or engineering
- entering data science from a non-computing major
- a choice of coursework, report, or thesis in a STEM-designated degree
This is a data science degree, not a machine learning degree. Only one machine learning or deep learning course is required, and artificial intelligence, data mining, and natural language processing are electives. The program is not offered online, and Michigan residents receive no tuition discount at the graduate level. Students who want a degree built entirely around AI, an online format, or lower resident tuition may want to compare other Michigan schools.
Official Michigan Technological University Program Links
- MS in Data Science program page
- Department of Data Science degree page
- Data Science MS course information
- Data Science graduate handbook
- Graduate cost of education
- 2026–27 graduate tuition schedule
Related Machine Learning Programs in Michigan
Students can also compare Michigan Technological University 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
- Oakland University – Rochester
- University of Michigan – Ann Arbor
- University of Michigan-Dearborn – Dearborn
- Wayne State University – Detroit
- Western Michigan University – Kalamazoo