Program Overview

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Master of Science in Public Policy and Management (MSPPM)

The Master of Science in Public Policy and Management (MSPPM) program at Heinz College is designed to train students to harness the power of data and analytic technologies to transform organizations that serve the public good. The program is offered in four distinct tracks: Flagship, Data Analytics, Washington, D.C., and Fast Track (Three-Semester).

Program Overview

The MSPPM program is a 2-year, 4-semester program that includes a required summer internship. The program is located in Pittsburgh, Pennsylvania.

Data Analytics Track

The Data Analytics track of the MSPPM program is the most quantitatively rigorous public policy program at Heinz College. The track is designed to train students to convert data into human-centered solutions. Students in this track will gain skills and techniques that open new possibilities for public policy research and social impact.

Curriculum

The curriculum for the Data Analytics track includes:

• Public Policy and Management Core:
  • Policy and Politics: American Political Institutions (90-714) or An International Perspective (90-713)
  • Applied Economic Analysis (90-710)
  • Accelerated Statistics (90-711)
  • Organizational Design and Implementation (94-700)
  • Writing for Public Policy (90-717)
  • Strategic Presentation Skills (90-718)
  • Database Management for Policy Analytics (90-838)
  • Optimization and Decision Modeling for Analytics (90-755)
  • Accounting and Finance Analytics (95-719)
  • Public Policy Capstone Project
• Data Analytics Core:
  • Python Programming (90-819)
  • Exploratory Data Analysis and Visualization in Python (90-800)
  • Applied Econometrics I (94-834)
  • Applied Econometrics II (94-835)
  • From Data to Action (94-867)
• Concentrations:
  • Students can elect an optional concentration in one of the following policy areas, or define their own:
    • AI Management
    • Energy and Environmental Policy
    • Health Policy
    • International Policy
    • Nonprofit and Public Management
    • Public Interest Technology
    • Social Policy
    • Technology Governance, Cybersecurity, and Privacy Policy
    • Urban & Regional Economic Development
    • U.S. Politics and Policy Making
• Sample Electives:
  • Policy Analysis and Practice (90-730)
  • Systems Analysis: Environmental Policy (90-798)
  • Resilient and Sustainable Communities (90-789)
  • Education Finance and Policy (90-817)
  • Federal Budget Policy (90-894)
  • Affordable Housing Policy and Finance (90-784)
  • Policy in a Global Economy (90-860)
  • Elective Politics and Policy-Making (90-754)
  • Generative AI: Applications, Implications and Governance (94-816)
  • Urban and Regional Economic Development (90-743)
  • Critical Analysis of Policy Research (90-822)
  • Working in the Policy Ecosystem (90-897)
  • Using R for Policy Data Analysis (90-872)
  • Machine Learning for Public Policy Lab (94-889)
  • Unstructured Data Analytics (94-775)
  • Data Science and Big Data (95-885)
  • Fundamentals of Operationalizing AI (94-879)
  • Demystifying AI (94-703)
  • Applied Ethical Analysis (94-883)
  • Python Programming (90-812)
  • Applied Econometrics (94-834 and 94-835)
  • International Crisis Negotiation Exercise (94-859)
  • Telling Stories with Data (94-870)
  • Policy Innovation Lab (90-783)
  • Design Thinking (94-866)
  • Behavioral Economics (90-880)
  • Program Evaluation (90-823)
  • Health Economics (94-705)
  • Evidence-Based Management (94-814)
  • Negotiation (94-800)
  • Public Finance (90-736)
  • Managing Analytic Projects (94-881)
  • Privacy Policy, Technology and the Law (95-818)
  • Cybersecurity Policy and Governance (95-744 and 95-743)

Sample Schedule

Below is one possible schedule for the Data Analytics track:

Year 1 - Fall Semester

• Applied Economic Analysis
• Intermediate Statistics
• Database Management for Policy Analytics
• Python Programming II OR Data Focused Python
• Exploratory Data Analytics and Visualization in Python

Year 1 - Spring Semester

• Optimization
• Decision and Risk Modeling
• Machine Learning Foundations with Python
• Applied Econometrics I and II

Year 2 - Fall Semester

• Decision Analytics for Business and Policy
• Organizational Design and Implementation
• Strategic Presentation Skills
• Accounting and Finance Analytics
• Machine Learning for Public Policy Lab
• Data Science and Big Data

Year 2 - Spring Semester

• Data Analytics Capstone Project
• Practical Unstructured Data Analytics
• Big Data and Large-Scale Computing
• Smart Cities: Growth and Intelligent Transportation Systems
• Critical AI Studies for Public Policy
• Geographic Information Systems

Careers

The Data Analytics track prepares students for careers in data analytics and public policy. Job titles and salary information for the Public Policy and Management: Data Analytics degree program are available.

STEM-Designated Program

The MSPPM program is a STEM-designated degree program, which provides students with the opportunity to apply for OPT STEM extensions.