Data Science Degree Programs

This is a partial list of degree programs at the University of Michigan, Ann Arbor, that focus on data science.

Graduate Programs

Masters in Data Science (Ann Arbor campus)
Offered through the College of Engineering (EECS), the College of Literature Science and the Arts (Statistics), the School of Public Health (Biostatistics), the School of Information, and the Michigan Institute for Data and AI in Society, this program provides core data science training focused on computer and information sciences, statistical sciences, and applications.

Read more

Data and Business Analytics Concentration
This program is designed for students looking to hone their analytical skills in an effort to provide data-driven business recommendations. Students are required to take 12 credits of analytics related courses. 

Read more

Masters in Data Science (Dearborn campus)
Offered through the College of Engineering & Computer Science, with four concentrations: computational intelligence, applications, business analytics, big data informatics. 

Read more

Masters in Applied Data Science Online
This online master’s program will be offered through the School of Information and Coursera.

Read more

Masters in Health Data Science (Ann Arbor campus)
Offered through the School of Public Health (Biostatistics), this program builds on the core of the MS in Biostatistics with emphasis on big data analytics and computing skills and applications in biomedical sciences and public health.

Read more

Undergraduate Programs

Undergraduate Degree in Data Science
Offered jointly through the College of Literature, Science and the Arts and the College of Engineering, this program provides a foundation in those aspects of computer science, statistics, and mathematics that are relevant for analyzing and manipulating large complex datasets.

Read more about the BS in Data Science
Read more about the BSE in Data Science

BS in Information: Information Analysis Path
The courses allow students to identify and articulate questions that matter to stakeholders, gather essential data, find answers that are grounded in empirical evidence, and present answers convincingly. 

Read more about the BSI Program

Programs with Data Science Components

Master of Science in Survey and Data Science
Survey methodology combines knowledge from sociology, psychology, statistics, and data science. Students take courses from each of these areas, and will specialize in Survey Methods, Survey Statistics, or Data Science. 

Read more

Graduate Certificate Program in Computational Discovery and Engineering 
This program trains students to conduct computationally intensive research, and prepares them for interdisciplinary research and product development that employ high-performance computing.

Read more

ICPSR Summer Program in Quantitative Methods for Social Research
This program offers over 80 courses on a broad range of methodologies and techniques that are relevant for research in the social, behavioral, and health sciences. 

Read more

Certificate in Survey Methodology 
Offered to graduate students in departments other than the survey methodology program, this is a two-year, part-time program. 

Read more

Ph.D. Program in Scientific Computing
The joint Ph.D. in Scientific Computing is intended for students who will make extensive use of large-scale computation, computational methods, or algorithms for advanced computer architectures in their studies.

Read more

The Data Science Student Experience

Watch U-M Data Science students give presentations to the 2020 NxtGen Summer Academy talking about the work and research they are doing in data science.

The Current State of Data Science

The Importance of Access in Data Science

Career Options/Professional Paths in Data Science

Community Data Science Project Examples

Experiential Learning

MIDAS organizes many events throughout the year specifically geared towards students’ technical skill development, job search and career preparation, and engagement with industry professionals in the data science field.


Participating as either teams or individuals, students use real world data sets from industry sponsors, community organizations, or University research projects to answer pre-defined research questions.  Often run as competitions, MIDAS aims to promote student work by using judges from industry that may (and many times do) offer outstanding participants internship and permanent job opportunities.

Previous Events:


Students learn about how data science is utilized in industry and how best to prepare for careers through conversations with real-world professionals.  Sessions are either centered around a theme (interviewing, company specific job openings, etc.) or feature panelists from various fields to give a broad overview of career opportunities in data science.

Previous Events: