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 or 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.

STEM Eligible

The Data Analytics certificate earned in tandem with the MPP degree is a STEM eligible program for international students.

Application Process

The certificate is open to any University of Chicago graduate student. Harris students please indicate your intent to pursue this certificate using the Harris Certificate Application Form 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:

• PPHA 30535 Data and Programming for Public Policy I
• PPHA 30536 Data and Programming for Public Policy II
• PPHA 30545 Machine Learning or BUSN 41204 Machine Learning or MACS 33002 Introduction to Machine Learning or CMSC 35300 Mathematical Foundations of Machine Learning

Please note: CMSC 35300 is designed for CS majors and CS PhD students; it is more challenging than the other listed course options.

Elective courses

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

• PPHA 34600 Program Evaluation
• PPHA 38829 Artificial Intelligence for Public 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
• BUSN 37304 Digital and Algorithmic Marketing