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. 

Harris certificates function as areas of specialization within the degree. Certificates assume knowledge of the 6-course Harris Core and build upon that foundation with coursework in specific policy areas or technical skills.

Students in the Master of Science in Computational Analysis and Public Policy (MSCAPP) program may not earn this certificate.

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. 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. No certificate course may be taken on a pass/fail grading basis. Students should complete the formal signup process to indicate their intention to pursue the certificate.

Required courses

Students must complete a two-course sequence of Data and Programming I and II:

• PPHA 30535 or PPHA 30537 Data and Programming for Public Policy I
• PPHA 30536 or PPHA 30538 Data and Programming for Public Policy II

Students must complete one of the following courses:

• PPHA 30545 or PPHA 30546 Machine Learning
• BUSN 41204 Machine Learning 
• CMSC 35300 Mathematical Foundations of Machine Learning
• MACS 33002 Introduction to Machine Learning
   

Elective courses

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

• PPHA 34600 Program Evaluation 
• PPHA 38829 Artificial Intelligence for Public Policy
• PPHA 42000 Applied Econometrics I 
• PPHA 42100 Applied Econometrics II 
• PPHA 60000 Policy Labs (with permission of the Certificate Director)
• BUSN 37304 Digital and Algorithmic Marketing
• BUSN 37105 Data Science for Marketing Decision Making
• BUSN 40206 Healthcare Business Analytics
• BUSN 41100 Applied Regression Analysis
• BUSN 41201 Big Data
• CAPP 30300 / PPHA 30581 Data Science Clinic
• ECMA 31130 Topics in Microeconomics

Certificate Contact

Dan Black, Interim Director

Peter Ganong, Certificate Director (on leave 23-24)