Undergraduate Degree in Data Science

The university offers an interdepartmental major in data science. The major combines computer science, statistics, and a student’s choice of advanced course work in any one of a number of different areas of computational science, including business, biology, earth and environmental science, political science and others.  The major consists of:

  • Prerequisite courses, which would typically be completed or in progress before declaring the major.
  • Core courses in Computer Science and Statistics. All are required.
  • Supplementary courses in Computer Science and Statistics.  These courses are not required, but are relevant to data science. 
  • Three upper-level courses in one application area (e.g.: Biology, Economics, Political Science, Earth & Environmental Science, etc.) OR three more upper-level courses (200 level+) in any mix of Computer Science and Statistics.  

In order to plan and declare your major, please see Michelle Saile, undergraduate coordinator for the Institute for Data Science.


  • MTH 150 Discrete Mathematics OR MTH 150A Discrete Math Module
  • MTH 161 Calculus I and MTH 162 Calculus II
          OR MTH 141, MTH 142, and MTH 143
          OR MTH 171Q and MTH 172Q
  • CSC 171 The Science of Programming OR AP credit OR programming experience

Core Courses

  • MTH 165 Linear Algebra with Differential Equations
  • STT 213 Elements of Probability and Mathematical Statistics
          OR STT 201 Introduction to Probability AND STT 203 Introduction to Mathematical Statistics
          OR STT 212 Applied Statistics for BIO and PHY Sciences
          OR STT 211 Applied Statistics for Social Sciences
  • STT 216 Applied Statistics II
  • STT 226W Introduction to Linear Models
  • CSC 172 The Science of Data Structures
  • CSC 240 Introduction to Data Mining
  • CSC 246 Machine Learning (pre req. CSC 242)

Supplementary Courses

  • CSC 282 Design and Analysis of Efficient Algorithms
  • CSC 242 Artificial Intelligence
  • CSC 296 Database Systems
  • CSC 248 Statistical Speech & Language Processing
  • CSC 249 Machine Vision
  • CSC 259 Big Data Computer Systems
  • ECE 206/CSC 266 GPU Programming using C/C++
  • ECE 207/CSC 267 Advanced GPU Programming
  • STT 277 Introduction to Statistical Software (2 credits) and STT 278 Methods of Data Analysis (2 credits)

Application Areas

Following are examples of application area course sets.  Many other sets of courses for these and other disciplines are possible.

Biology: Genetics

  • Additional Prerequisites: BIO 110-111 or BIO 112-113
  • BIO 198 Genetics OR BIO 190 Genetics
  • BIO 253 Computational Biology
  • BIO 265 Molecular Evolution

Environmental Science

  • Additional Prerequisites: EES 101 and CHM 131
  • EES 211 Geohazards and Their Mitigation: Living on an Active Planet
  • EES 212 A Climate Change Perspective to Chemical Oceanography
  • EES 215 Environmental and Applied Geophysics


  • Additional Prerequisites: ECO 108 or AP Credit
  • ECO 207 Intermediate Microeconomics
  • MKT 203 Principles of Marketing
  • ECO 231 Econometrics

Political Science

  • PSC 203 Survey Research Methods
  • PSC 204 Research Design
  • PSC 215 American Elections