Data Science

The rapidly expanding collection of massive amounts of data is leading to transformations across broad segments of industry, science, and society. These changes have sparked great demand for individuals with skills in managing and analyzing complex data sets. Such skills are interdisciplinary, involving ideas typically associated with computing, information processing, mathematics, and statistics as well as the development of new methodologies spanning these fields. Our major in Data Science (offered jointly with the Dietrich School of Arts & Sciences Departments of Mathematics and Statistics) will enable students to participate in this data revolution.

This undergraduate major allows students to gain critical skill sets that span key areas of statistics, computing, and mathematics, with foundational training providing literacy in four areas (data, algorithmic, mathematical, and statistical) that every student needs to master data science. Students will develop expertise that connects theory to the solution of real-world problems, and be able to specialize their studies towards a more specific career focuses. Completing this major will prepare students to work as a data science professional or to pursue graduate study in a direction involving data in a significant way.

Major Requirements

Foundational Courses

All of the following courses are required, except as noted.

Expertise Courses

All of the following courses are required, except as noted.


Students within the data science major will have the opportunity to pursue an area of specialization through the selection of elective courses in a targeted direction relating to data analytics, computer systems, modeling, or data science in context. While selecting all 3 courses from the same category is advised for students seeking a focus, students may also choose courses across categories to suit their interests, if they prefer that approach. The specialization course groupings are as follows.

  • Computer Systems: Students pursuing this specialization will gain depth of knowledge in the development, deployment, and analysis of the complex computer and information systems necessary for tackling large-scale data science problems.
  • Data Analytics: Students pursuing a data analytics specialization will enhance their ability to make sound inferences and decisions using the science and art of learning from data: specifically, the design, collection, analysis, and interpretation of data in an uncertain world, and the communication of findings.
  • Data Science in Context: Students pursuing this specialization will gain depth of knowledge in both the technical and organizational aspects of the management, curation, description, preservation, and application of digital datasets of varying sizes in specific business, professional, or scientific contexts. We expect the collection of courses within the specialization to expand as more domain-specific data science courses begin to be offered across campus.
  • Modeling: Students pursuing a modeling specialization will enhance their ability to develop and harness theoretical tools to characterize structure within data and to represent and analyze processes that may underlie this structure.


Select a capstone course, relevant to the chosen specialization, from the following list.

For full major requirement details, visit the Data Science course catalog.

Admissions Requirements