Secondary Field Requirements

To earn the Secondary Field in Data Science students must complete a Plan of Study with five courses meeting the requirements below and pass a short oral examination by a faculty committee.

Each student's plan of study for the Secondary Field will include:

  1. Core Courses

At least 3 of the Data Science core courses:

  • AC 209a*         Data Science 1: Introduction to Data Science
  • AC 209b*         Data Science 2: Advanced Topics in Data Science
  • AM 207            Advanced Scientific Computing: Stochastic Methods for Data Analysis, Inference, and Optimization
  • AC 207            Systems Development for Computational Science
  • AC 221            Critical Thinking in Data Science

*In certain circumstances, students can count CS 109a/b in place of AC 209a/b.

  1. Electives

Two electives in Computer Science or Statistics. Students may choose from a wide variety of elective courses offered by the Computer Science and Statistics faculties. A list of suggested electives can be found here.

Alternatively, students may choose to satisfy the elective requirement by taking additional core courses. Students may also choose, as a substitute for one elective, either AC 297r (the Data Science Capstone Project course), or four credits (two semesters) of AC298r (the Interdisciplinary seminar in Computational and Data Science).

Upon completion of required coursework, each candidate for the Data Science Secondary Field will be required to give an oral presentation on a data science research project - typically a small part of the student’s doctoral thesis work or a data-focused side project they have worked on in their lab. Students will be expected to display achievement of the Data Science program’s learning outcomes, including the ability to communicate their work in an interdisciplinary context. 

SEAS will organize a Secondary Field presentation event once each semester.