Computational Public Policy

The concentration in Computational Public Policy focuses on students developing skills in computer science, data science, and advanced statistics combined with policy analysis. It focuses primarily, although not exclusively, on the application of quantitative techniques to policy issues that arise in various subject matter areas. Because policy analysis interacts with the technical elements of particular disciplines, all schools and many departments in the University offer courses that meet these requirements. For the most part, the common denominator is the extensive use of machine learning and artificial intelligence, and statistics, as policy analysis tools. Concentration courses should focus on developing the skills necessary for modern data-intensive policy analysis. Students choosing such courses, therefore, need to consider their interest in the field in which the course is being given in addition to the methodology being presented. It is also advisable in the majority of the recommended courses that concentrators have an above average background in mathematics, statistics and computation.

Courses

See the Stanford Bulletin for the list of approved concentration courses. Note that this is not an exhaustive list; students may select other courses for their concentration with the approval of their faculty advisor.