Turn Raw Data Into Solutions for Society’s Most Pressing Problems
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.
Our MSPPM: Data Analytics pathway will 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)
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:
At Heinz College, students learn by engaging with the real world—while under the tutelage of our trail-blazing faculty. Heinz's Policy Innovation Lab provides 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.
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.
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.
Jafar Haider came back to grad school looking for a challenge. In MSPPM: Data Analytics, he gained a new network, a new skillset, and a whole new outlook.
For detailed curriculum information, please visit the MSPPM: Data Analytics Student Handbook.
Below is one possible schedule for MSPPM: Data Analytics. Actual schedules will vary depending on pathway and electives.
Class titles in bold are core courses. Heinz College offers a mix of full-semester (14 weeks) and half-semester courses (7 weeks) for core and elective courses.
--REQUIRED SUMMER INTERNSHIP--
*Half-semester courses
Job titles and salary information for the MSPPM-DA program.
Compare all four MSPPM options at a glance
The MSPPM program is offered in four distinct modalities—Pittsburgh (Two-Year), Data Analytics, Washington D.C., and Fast Track (Three-Semester). Compare all four and choose the path that best suits your mission.
