Heinz College’s analytics coursework is unrivaled among policy schools, and the MSPPM: Data Analytics pathway is our most quantitatively rigorous public policy program.
As the modern world generates massive amounts of data, large organizations, government agencies, think tanks, and consulting firms all seek the brightest minds with next-generation data skills. The need continues to grow in public-interest sectors for professionals who can interpret and analyze raw data to improve public programs
and policies across areas such as education, transportation, energy and the environment, criminal justice, sustainable development, national security and defense, and health and human services.
You can step up and take on such challenges.
OurMSPPM: Data Analyticspathwaywill train you to harness the power of data and analytic technologies to transform organizations that serve the public good. MSPPM-DA graduates have a unique skill set in the policy field and are highly sought by employers, including the top firms and agencies in our partner network.
In addition to world-renowned faculty with deep expertise in analytics, Heinz College houses several analytics-driven research institutes, where you can get involved in groundbreaking data projects while in school.
Location: Pittsburgh, Pennsylvania
Duration: 2 years / 4 semesters (Fall, Spring, Summer Internship, Fall, Spring)
MSPPM Admissions Requirements
life at heinz
From Instagram takeovers to campus visitors, from experiential learning to student clubs to the vibrant city of Pittsburgh we call home, see all that Heinz College has to offer.
Policy makers regularly engage with Heinz College and our expert faculty. This includes U.S. Secretary of Transportation Pete Buttigieg, who visited to discuss the future of transportation and the role AI will play in the field. He also interacted with students during his visit. Learn more about Buttigieg's visit.
Data Science for Social Good &Public Interest Technology
Heinz College is a global leader in applying data science to public policy and using technology for public good. Among policy schools, we have the deepest bench of data scientists and analytics experts to help you convert data into human-centered solutions. Under the direction of our faculty experts, our policy analytics students tackle complex problems such as:
- Predicting resource shortages at senior care facilities during COVID-19
- Promoting fairness and reducing bias in criminal sentencing
- Combatting the opioid crisis by helping social workers identify abuse
- Improving transparency and data-sharing across public service agencies
- Mapping public utilities using data and technology
- Reducing waste and fraud in the Medicare system
- Using text analytics and machine learning to fight poaching and illicit trade
- Testing feasibility of large-scale projects in renewable energy, like solar farms and biogas
- Preventing homelessnesswith predictive analytics
At Heinz College, students learn by engaging with the real world—whileunder the tutelage of our trail-blazing faculty. Heinz'sPolicy Innovation Labprovides students with an avenue to gain real-world experience as they earn their master's degree.
The Policy Innovation Lab is an intensive, applied course that prepares students to become public-interest technologists who are creative, ethical, inclusive, and responsive. Our faculty teach students how to design and build public-interest technology services with human-centered design. Working directly with a client from a government office or public-service nonprofit, students aim to develop and deliver a Minimum Viable Product (MVP) with high-impact results.
Game-Changing Research
MSPPM-DA students gain data skills and techniques that open new possibilities for public policy research and social impact. Heinz College and CMU provide many opportunities to apply those skills on innovative projects directed by our faculty and sponsored by our renowned research centers. This experiential learning takes place at the intersection of policy and technology, allowing students to bring the full weight of data analytics to bear on the public policy issues of today and tomorrow.
My Story: Curt
Curt Williams chose the MSPPM-DA program to augment his statistics background, as well as add Python and R to his repertoire.
My Story: Ricardo
Ricardo Gil became interested in public policy through the lens of issues he saw in Mexico, such as poverty and income inequality.
My Story: Nikita
Nikita Setia loved working with data at a nonprofit in India providing safe spaces for young women. The MSPPM: Data Analytics program helps her make a bigger impact.
MSPPM: DATA ANALYTICS CURRICULUM
- MSPPM Core
- Intermediate Statistics* (90-777)
- Applied Economic Analysis (90-710)orIntermediate Economic Analysis (90-709)
- Management Science (90-722)
- Policy and Politics: American Political Institutions (90-714)or International Perspective (90-713)
- Accounting and Finance Analytics* (95-719)
- Organizational Design and Implementation* (94-700)
- Writing for Public Policy* (90-717)
- Strategic Presentation Skills* (90-718)
- Intermediate Programming with Python* (90-819)
- Exploratory Data Analysis and Visualization in Python* (90-800)
- Machine Learning Foundations with Python (90-803)
- Database Management for Policy Analytics (90-838)
- Policy & Politics: An International Perspective (90-713)
- Optimization (90-722)
- Decision and Risk Modeling (90-760)
- Applied Econometrics I (94-834)
- Applied Econometrics II (94-835)
- Machine Learning Foundations with Python (90-803)
- Organizational Design & Implementation (94-700)
- Decision Analytics for Business and Policy (94-867)
- Strategic Presentation Skills (90-718)
- Financial Statements (90-723)
- Data Analytics Capstone Project
PLUS
- Required Summer Internship
*Half-semester courses
For class, syllabi, and course information, please visit the Heinz College course catalog.
- Data Analytics Coursework
Data AnalyticsCoursework is takenin addition toMSPPM Core listed below.
MSPPM-DA Requires a Minimum of 24 Units Taken Across the Following Three Areas:
(Note: courses listed are only a sample of analytics coursework)
Machine Learning
- Machine Learning for Public Policy Lab (94-889)
- Practical Unstructured Data Analytics (94-775)
- Data Science and Big Data (95-885)
- Introduction to Artificial Intelligence (95-891)
Computer Programming and Analytics
- Decision Analysis and Multi-criteria Decision Making (94-833)
- Big Data and Large-Scale Computing (95-869)
- A/B Testing, Design and Analysis (95-819)
- Exploring and Visualizing Data (95-868)
- Programming R for Analytics (94-842)
- Geographic Information Systems (94-802) OR Health Care Geographic Information Systems (90-834)
- NoSQL Database Management (95-737)
- Advanced Business Analytics (95-866)
- Linux and Open Source (95-799)
- Advanced Geographical Information Systems (90-753)
- Healthcare Information Systems (94-706)
- SAS for Public Policy (94-827)
- R Shiny for Operations Management (94-880)
- Advanced Relational Database Management (95-736)
- Introduction to Information Security (95-752)
- Applied Threat Analytics (95-889)
Policy Methods and Ethical Frameworks
- Policy Innovation Lab: Public Interest Technology (90-783)
- Lean Innovation Lab (94-891)
- Policy Analysis in Practice (90-730)
- Methods of Policy Analysis: The Future of Work (90-745)
- Applied Ethical Analysis (94-883)
- Critical AI Studies for Public Policy (90-769)
- Program Evaluation (90-823)
- Smart Cities: Growth and Intelligent Transportation Systems (94-845)
- Quantitative Analysis of Income Inequality (90-712)
- Cost Benefit Analysis (90-747)
- Critical AI Studies for Public Policy (90-769)
- Policy Innovation Lab: Public Interest Technology (90-783)
- Critical Analysis of Policy Research (90-822)
- Policy in a Global Economy (90-860)
- Behavioral Economics in Public Policy (90-882)
- Econometrics I (PhD) (90-906)
- Econometric Theory and Methods (PhD) (90-907)
- Introduction to Decision Analytics and Systems (94-716)
- Privacy in the Digital Age (94-806)
- Design Thinking (94-866)
- Managing Analytic Projects (94-881)
- Intro to Transportation Systems Analysis (94-893)
- Policies of Wireless Systems (95-824)
For class, syllabi, and faculty information, please visit the Heinz College course catalog.
- MSPPM Sample Electives*
- Telling Stories with Data (94-870)
- Systems Analysis: Environmental Policy (90-798)
- Resilient and Sustainable Communities (90-789)
- Technology, Humanity and Social Justice - Education (94-783)
- Poverty, Inequality and Social Policies: An International Comparison (90-471)
- International Crisis Negotiation Exercise (94-859)
- Behavioral Economics (90-880)
- Program Evaluation (90-823)
- Policy in a Global Economy (90-860)
- Elective Politics and Policy-Making (90-754)
- Health Economics (94-705)
- Organizational Change (91-809)
- Evidence-Based Management (94-814)
- Negotiation (94-800)
- Privacy in the Digital Age (94-806)
- Policies of Wireless Systems (95-824)
- Measuring Social (94-823)
- SAS for Public Policy (94-827)
- 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)
*Elective availability may differ by pathway/location; students may also enroll in graduate-level courses from other Heinz College programs as well as other departments across Carnegie Mellon University’s campus, with approval.
For class, syllabi, and faculty information, please visit the Heinz College course catalog.
For detailed curriculum information, please visit theMSPPM: Data Analytics Student Handbook.
SAMPLE SCHEDULE
Below is one possible schedule for MSPPM: Data Analytics. Actual schedules will vary depending on pathway and electives.
Class titlesin bold arecore courses. Heinz College offers a mix of full-semester (14 weeks) and half-semester courses (7 weeks) for core and elective courses.
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*
--REQUIRED SUMMER INTERNSHIP--
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
*Half-semester courses
yearly reports
Job titles and salary information for the MSPPM-DA program.
MSPPM-DA Reports
Frequently Asked Questions
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