Data Science for Public Policy, MS

Modality

On Campus

Program URL

https://mccourt.georgetown.edu/master-of-science-in-data-science-for-public-policy/

The Master of Science program in Data Science for Public Policy is a dynamic combination of the McCourt School’s renowned policy analysis curriculum and state-of-the-art data science courses. The program enhances students’ analytical skills and provides the necessary knowledge and experience to expertly design and manage effective public policy. Students develop vital skills in collaboration, critical thinking, economic analysis, ethical leadership, and policy analysis through McCourt’s Foundational Skills. With a focus on fostering a deep understanding and application of sound policy principles, graduates are empowered to tackle complex policy challenges in the real world.

Academic Policies

The academic policies and procedures of the Data Science for Public Policy program are those specified in Georgetown’s University Bulletin.

Program Requirements

The Data Science for Public Policy program requires 39 credits that are divided into core courses, elective courses, and seminars.

Course List

Code	Title	Credits
Core Courses
PPOL 5200	Accelerated Stat for Pub Pol I	3
PPOL 5201	Accelerated Stat for PubPol II	3
PPOL 5004	Intermediate Microeconomics	0-3
PPOL 5006	The Politics of Policy-Making	3
or PPOL 5007	Comp Politics of Policy-Making
PPOL 5008	Public Management	3
or PPOL 5009	Mgmt & Implem in Dev Countries
PPOL 5202	Data Visualization for Data Sc	3
PPOL 5203	Data Science I: Foundations	3
PPOL 5204	Data Science II: App Stat Lng	3
PPOL 5205	Data Science III: Adv Mod Tec	3
PPOL 5206	Massive Data Fundamentals	3
PPOL 5207	Data Ethics	1.5
PPOL 5208	Communication for Data Science	1.5
Elective Courses
The remaining 6 credits can come from any course offered within either the McCourt School of Public Policy or the Graduate School’s Data Analytics program.		6
Total Credits		36-39