Master of Science in Public Policy Data Science

Program Director (Data Science): Yolanda Gil, PhD
Program Co-Director (Public Policy): T.J. McCarthy, PhD

The Master of Science in Public Policy Data Science is a cross-disciplinary joint degree program offered jointly between the Viterbi School of Engineering and the Sol Price School of Public Policy. Students complete a core set of courses to provide a foundation in data science and public policy and choose electives to optimize their preparation for their preferred career path and unique professional opportunities. This program blends fundamentals of data science with public policy and uniquely prepares students for careers in government agencies to leverage new data technologies to inform public policy decision-making.  The increasing availability of data is revolutionizing the way many agencies operate, particularly with respect to governance transparency and accountability, law enforcement, transportation and housing policy.  This is causing profound changes in strategies for crime-fighting, defense, national intelligence, social programs, and finance and operations of agencies. The effective use of data science holds the potential to revolutionize how public policy is created.

The curriculum is designed to be accessible to students with any background, including students with a public policy background and no computer science knowledge as well as students with a computer science background and no public policy knowledge.  Students with undergraduate degrees in computer science, engineering, science or mathematics will acquire the necessary knowledge to analyze health data with diverse sources and purposes and can request to replace introductory data science courses with more advanced ones.  Students with undergraduate degrees in public policy, political science, economics, and other social sciences will acquire formal and practical data science skills and can request to substitute introductory courses in public policy with more advanced ones.  There is no requirement of prior knowledge of programming or computer science, as the curriculum is designed with special introductory courses that are accessible to students with diverse backgrounds.

 Students will learn a range of data science skills such as developing scalable data systems, using state-of-the-art software and infrastructure for data science, designing data analyses with statistical methods, applying machine learning and data mining techniques, designing effective visualizations, and working in multi-disciplinary data science teams. They will also learn the foundations of economics, cost-benefit analysis, and statistical and econometric methods that should be coupled to effectively analyze public policy challenges, and inform and guide public policy decisions.  Through a capstone project, students will work in groups to produce a consulting-style report, which will demonstrate their capabilities and skills for the job market.

Prospective students can refer to the Price website for more information about the program.

All information contained here is summarized from the USC Catalogue and is considered non-official. For all rules, regulations, procedures, and outlines, please see the current academic year USC Catalogue. The USC Catalogue supersedes all other publications.

Current students follow degree requirements in effect for the academic year they began their studies at USC.  If you are a current student, please refer to your STARS report or the appropriate USC Catalogue for your year.  Students seeking to advance their catalogue year to follow updated curricula may contact their department advisor.

Published on July 17th, 2018

Last updated on October 19th, 2022