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Academics

PhD in Data Science

Our doctoral program combines the aspiration to train all students in mathematical foundations of Data Science, responsible data use and communication, and advanced computational methods, with an appreciation for the diverse research interests of the data science faculty. 

First Year Requirements

The standard first year program requires students to complete 9 courses total: 4 required classes; 1 class either in mathematical foundations or scalability & computing, and 4 graduate-level elective classes that can come from our catalogs in Data Science, Statistics, Computer Science, or other departments around the university. Click here to view more information about our required courses and potential elective options here at UChicago. Some students, after consulting with the graduate advisor, may decide to spread their 9 courses over the first two years in the PhD program.

 

All PhD students will take the required classes below. Each one is designed to be completed in-person here at our Hyde Park campus:

 

  1. DATA 31500: Data Interaction
  2. DATA 34100: Introduction to Data Systems & Data Design
  3. DATA 35900: Responsible Use of Data and Algorithms
  4. DATA 37711: Foundations of Machine Learning & AI – Part 1
  5. DATA 37712: Foundations of Machine Learning & AI – Part 2  OR  DATA 34200: Data Engineering & Scalable Computing

 

Synthesis Project

Students will take courses during the first two years after which they focus primarily on their research. A milestone in this transition is completion of a synthesis project before the end of the second year in the program. Thesis projects can be done in partnership with any of DSI affiliates and aims to meaningfully connect PhD students to their chosen focus areas.

 

Thesis Advisor & Dissertation Committee

Students typically select a thesis advisor by the beginning of their second year. By the end of the third year, each PhD student, after consultation with their advisor, shall establish a thesis committee of at least three faculty members, including the advisor, with at least half of the members coming from the Committee on Data Science (CODAS).

 

Proposal Presentation & Admission to Candidacy

By the end of the third year, students should have scheduled and completed a proposal presentation to their committee in order to be advanced to candidacy. The proposal presentation is typically an hour-long meeting that begins with a 30-minute presentation by the student followed by a question and discussion period with the committee.

 

Dissertation Defense

The PhD degree will be awarded to candidates following a successful defense and the electronic submission of the final version of the dissertation to the University’s Dissertation Office.

 

Teaching Assistantships (TA)

PhD in Data Science students have a a minimum requirement of 2 teaching assignments over the course of their degree completion. Depending on their subfield/research area, a student may hold up to 3 quarters of teaching each year; no student will be required to teach more than 3 times each academic year. Students who hold more than 3 teaching assignments in an academic year will receive additional compensation above their primary funding amount.