Specializations Data Analytics Specialization Education Policy Specialization Energy & Environmental Policy Specialization Finance & Policy Specialization Gender and Policy Specialization Global Conflict Studies Specialization Health Policy Specialization International Policy & Development Specialization Markets & Regulation Specialization Municipal Finance Specialization Social and Economic Inequality Specialization Survey Research Specialization Certificates Outside Harris 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 specialization seeks to prepare students for careers where data analysis plays a central role.Students who complete this specialization will be able to:Write simple programs in R or PythonLearn modern tools for data management, analysis, and presentation, including github, matplotlib, pandas, R, and SQLConstruct and clean data sets from disparate sources and understand how to summarize and visualize modern data setsUse modern, computationally intensive methods to analyze data for the evaluation of policyThe specialization's menu of electives is designed to allow students to increase their exposure to analytical methods used in the evaluation of public policy. Harris specializations function as areas of focus within the degree. Specializations 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 specialization.Application ProcessThe specialization is open to any University of Chicago graduate student. Harris students please indicate your intent to pursue this specialization using the Harris Specialization Application Form.For specialization registration questions, please reach out to email@example.com.Planning for the SpecializationFor information on which quarter(s) each course will be offered see the Harris Courses page and filter by specialization. For courses offered by other divisions the typical quarter(s) offered has been indicated.Specialization RequirementsThe specialization 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 specialization course may be taken on a pass/fail grading basis. Students should complete the formal signup process to indicate their intention to pursue the specialization.Required coursesStudents must complete a two-course sequence of Data and Programming I and II:PPHA 30535 or PPHA 30537 Data and Programming for Public Policy IPPHA 30536 or PPHA 30538 Data and Programming for Public Policy IIStudents must complete one of the following courses:PPHA 30545 or PPHA 30546 Machine LearningBUSN 41204 Machine Learning CMSC 35300 Mathematical Foundations of Machine LearningMACS 33002 Introduction to Machine Learning Elective coursesStudents must complete one of the following courses to fulfill the four-course requirement:PPHA 34600 Program Evaluation PPHA 38829 Artificial Intelligence for Public PolicyPPHA 42000 Applied Econometrics I PPHA 42100 Applied Econometrics II PPHA 60000 Policy Labs (with permission of the Specialization Director)BUSN 37304 Digital and Algorithmic MarketingBUSN 37105 Data Science for Marketing Decision MakingBUSN 40206 Healthcare Business AnalyticsBUSN 41100 Applied Regression AnalysisBUSN 41201 Big DataCAPP 30300 / PPHA 30581 Data Science ClinicECMA 31130 Topics in MicroeconomicsSpecialization ContactDan Black, Interim DirectorPeter Ganong, Specialization Director (on leave 23-24)Peter GanongEmail firstname.lastname@example.orgAssociate ProfessorPeter Ganong Peter Ganong studies how households manage difficult financial circumstances such as unemployment and having an underwater mortgage.