Data Science Joint Major

Data Science Program Faculty

Professor Iwan Praton, Co-Chair (Fall 2025)

Professor Aaron Howard, Co-Chair (Fall 2025), Chair (Spring 2026)
 

Members of the Data Science Program Committee

Bennett Helm
Elijah E. Kresge Professor of Philosophy

Christina Weaver
Carmie L. and Beatrice J. Creitz Professor of Mathematics

Jaime Blair
Professor of Biology

Iwan Praton
Professor of Mathematics

David Ciuk
Associate Professor of Government

Danel Draguljić
Associate Professor of Mathematics

Thomas Hull
Associate Professor of Applied Mathematics

Nick Kroll
Associate Professor of Philosophy

Ed Novak
Associate Professor of Computer Science

Ryan Trainor
Associate Professor of Physics

Justin Brody
Assistant Professor of Computer Science

Emily Jensen
Assistant Professor of Computer Science

Yi-ching Lee
Assistant Professor of Mathematics

Willie Wilson
Assistant Professor of Computer Science

Aaron Howard
Senior Teaching Professor of Biology

Additional faculty not on the program committee also contribute to this program.

A Joint Major in Data Science consists of 8 courses:

• DSC 115 - Introduction to Data Science Credits: 1
• MAT 109 - Calculus I Credits: 1 (or other calculus course)
• MAT 215 - Intro to Statistical Modeling Credits: 1

•  

• AND Either:

• CPS 173 - Introduction to Computer Programming AND CPS 111  - Computer Science I

• OR

• CPS 111 - Computer Science I Credits: 1
• CPS 112   - Computer Science II  

•  

• AND

• A statistics course approved by the Program Chair

• AND

• Two electives from the pre-approved lists or as approved by the Program Chair

•  

• NOTE: Due to the overlap of content and required courses, Data Science cannot be combined in a joint major with Computer Science.

Data Science Courses

• CORE COURSES:

• CPS 111 - Computer Science I Credits: 1
• CPS 112 - Computer Science II Credits: 1
• CPS 222 - Computer Science III Credits: 1
• MAT 109 - Calculus I Credits: 1
• MAT 110 - Calculus II Credits: 1
• MAT 111 - Calculus III Credits: 1
• DSC 115 - Introduction to Data Science Credits: 1
• MAT 115 - Introduction to Data Science Credits: 1
• DSC 215 - Intro to Statistical Modeling Credits: 1
• MAT 215 - Intro to Statistical Modeling Credits: 1
• MAT 216 - Probability and Statistics I Credits: 1
• MAT 229 - Linear Algebra and Differential Equations Credits: 1

•  

• ELECTIVE COURSES:

• AMS 385 - Gender at Work Credits: 1
• BIO 362 - Data Science in Ecology and the Environment Credits: 1
• BOS 335 - Business and the Natural Environment Credits: 1
• CPS 261 - Algorithms Credits: 1
• CPS 360 - Introduction to Machine Learning Credits: 1
• CPS 363 - Introduction to Bioinformatics Credits: 1
• CPS 367 - Artificial Intelligence Credits: 1
• FLM 332 - Documentary History and Practice Credits: 1
• GOV 350 - Science Gone Wrong: Fraud, Breaches of Integrity, and the Misuse of Statistics Credits: 1
• GOV 352 - Global Justice Credits: 1
• HIS 351 - China and the Global Environmental Crisis Credits: 1
• MAT 316 - Probability and Statistics II Credits: 1
• MAT 323 - Stochastic Processes Credits: 1
• MAT 416 - Design and Analysis of Experiments Credits: 1
• PHI 223 - Biomedical Ethics Credits: 1
• RST 339 - Religion and the Brain Credits: 1
• SOC 210 - Class, Status & Power Credits: 1
• SOC 330 - Sociology of Medicine Credits: 1
• SOC 345 - Sociology of Sexuality Credits: 1
• SOC 350 - Intersectional Approaches to the Sociology of Gender Credits: 1
• SOC 360 - Race and Ethnic Relations Credits: 1
• STS 311 - History of Medicine Credits: 1