Data Science—MS

The Michigan Tech Advantage

The Michigan Tech Data Science MS provides a broad-based education in data mining, predictive analytics, cloud computing, data-science fundamentals, communication, and business acumen. You'll gain a competitive edge through domain-specific specialization in disciplines of science and engineering, and you'll have the freedom to explore and develop your own interests in one or more domains. 

Navjot Kaur

"The best parts of Computing[MTU] are the quality of the coursework and the helpful nature of the  professors."

Navjot Kaur, Data Science Student

Program Prerequisites

Entry into the Data Science MS program assumes basic knowledge in statistical and mathematical techniques, computer programming, information systems and databases, and communications, obtained through a degree in business, math, computing, science, or an engineering discipline.

Past Coursework Requirements

Each year we evaluate and adjust our course lists, the coursework requirements for prior years are linked below.

Current Coursework Requirements

Our Master of Science in Data Science is a terminal degree designed to prepare students for careers in industry and government.

Students in the Data Science program take courses from four categories: Core Courses, Elective Courses, Foundational Courses, and Domain Specific/Elective courses.

Core Courses—12 credits

Foundational Courses—Maximum of 6 credits

A maximum of six credit hours of foundational skills courses at the 3000–4000 level may be applied to the Master of Science in Data Science. These courses will build skills necessary for successful completion of the MS in Data Science. Some students will not need to take these foundational courses and will instead use the domain electives to reach the credit requirements of this program.

Electives—Minimum of 6 credits

Two courses must be taken from the list of approved elective courses:

Domain Specific Courses—Maximum of 12 Credits

To complete the Master of Science in Data Science, students must earn the remaining of the required 30 credits through completion of approved domain-specific Data Science courses. Students may choose domain-specific courses from one or more domains. Each student will consult with her/his advisor in order to determine the appropriate mix of elective courses and domain-specific courses, given the student’s background, interests, and career aspirations.

Biomedical Engineering

Business and Economics

Chemistry

Cognitive and Learning Sciences

Computer Sciences

Electrical and Computer Engineering

Forest Resources and Environmental Science

Geological and Mining Engineering and Sciences

Mathematics

Mechanical Engineering-Engineering Mechanics

Physics

Social Sciences

Applied Computing

Co-Op

Sample Schedules