With increased digital access to data and the development of powerful, but inexpensive, computing, in the 21st century the formulation and evaluation of public policy is more and more reliant on the analysis of data. This certificate seeks to prepare students for careers where data analysis plays a central role.

Students who complete this certificate will be able to:

• Write simple programs in R and Python

• Learn modern tools for data management, analysis, and presentation, including github, matplotlib, pandas, R, and SQL

• Construct and clean data sets from disparate sources and understand how to summarize and visualize modern data sets

• Use modern, computationally intensive methods to analyze data for the evaluation of policy

The certificate's menu of electives is designed to allow students to increase their exposure to analytical methods used in the evaluation of public policy.

Application Process

The certificate is open to any University of Chicago graduate student. Harris students please indicate your intent to pursue this certificate during the application period open in October and June of each academic year. If you are a non-Harris student and intend to complete the requirements for the Data Analytics certificate please submit the Harris Certificate Application for Non-Harris Students to indicate you are pursuing this certificate. 

Planning for the Certificate

For information on which quarter(s) each course will be offered see the Harris Courses page and filter by certificate. For courses offered by other divisions the typical quarter(s) offered has been indicated.

Certificate Requirements

The certificate requires completion of three required courses, along with one additional course (four courses total). Students must achieve at least a B- grade in each course, and there is no pass/fail option. Students should contact their advisor to indicate their intention to pursue the certificate.

Required courses

Students must complete the following three course sequence (for students entering in 2018-2019):

• PPHA 30550 Introduction to Programming for Public Policy (Spring 2019)
• PPHA 30531 Data Skills for Public Policy (Autumn 2019)
• PPHA 30545 Machine Learning (Winter 2020)

Students must complete the following three course sequence (for students entering in 2019-2020):

• PPHA 30535 Data and Programming for Public Policy I (Spring 2020)
• PPHA 30536 Data and Programming for Public Policy II
• PPHA 30545 Machine Learning

Elective courses

Students must complete one of the following courses to fulfill the requirement:

• PPHA 34600 Program Evaluation
• PPHA 38820 Machine Learning and Policy
• PPHA 41400 Applied Regression Analysis
• PPHA 42000 Applied Econometrics I
• PPHA 42100 Applied Econometrics II
• PPHA 60000 Policy Labs projects, with permission of certificate head