The Master of Science in Data Science Public Policy (MS-DSPP) is a 39-credit degree program, divided into core (required) courses, elective courses, and seminars.

  • Type of Degree

    Master’s Degree

  • Format

    On-Campus, Full-time

  • Length

    2 Years

  • Department

    MS-DSPP Programs

Core Courses Anchor

Core Courses

The core courses emphasize analytical skills and core knowledge for designing and managing sound public policy.

Quantitative Social Sciences (6 credits)

  • PPOL 560 Accelerated Statistics for Public Policy I (3 credits)
  • PPOL 561 Accelerated Statistics for Public Policy II (3 credits)

Foundations of Public Policy (9 credits)

  • PPOL 506 Intermediate Microeconomics I (3 credits)
  • PPOL 510 Policy Process; or PPOL 511: Comparative Policy Process (3 credits)
  • PPOL 514 Public Management; or PPOL 515: Comparative Public Management (3 credits)

Civic Data Science (15 credits)

  • PPOL 563 Data Visualization (3 credits)
  • PPOL 564 Data Science I: Foundations (3 credits)
  • PPOL 565 Data Science II: Applied Statistical Learning (3 credits)
  • PPOL 566 Data Science III: Advanced Modeling Techniques (3 credits)
  • PPOL 567 Massive Data Fundamentals (3 credits) or PPOL 740: Relational Database Sys & SQL (3 credits)

Ethics and Law (1.5 credits)

Communication (1.5 credits)

  • PPOL 569 Communication for Data Science (1.5 credits)
Back to Top
McCourt’s Foundational Skill Set Anchor

McCourt’s Foundational Skill Set

In 2018, McCourt organized a Curriculum Innovation Committee to review and modernize the core curricula of our Masters degree programs. Over the past three years, the committee worked toward a number of goals, including developing a set of core competencies for all McCourt degree programs.

After reviewing the core curriculum, benchmarking other policy schools, and speaking with employers, and alumni, the committee developed a set of core competencies which were discussed, voted on, and approved by the McCourt School faculty.

All McCourt students graduate with the following foundational skills:


  • Collaboration
  • Critical Thinking
  • Economic Analysis
  • Engaging with Bias
  • Ethical Leadership and Management
  • Evaluation
  • Policy Analysis
  • Political Analysis
  • Quantitative Reasoning
  • Strategic Communication
Back to Top
McCourt Foundations Anchor

McCourt Foundations

In the fall of 2020, the McCourt School launched a new experiential learning program which seeks to lay the foundation for a McCourt degree. 

McCourt Foundations is designed to facilitate the transition to graduate school, introduce incoming students to a set of core leadership and communications skills, and catalyze equity-centered policy work and advocacy. An experiential program led by McCourt faculty, staff, and Leadership Fellows, McCourt Foundations builds the skills and confidence necessary to design, implement, and measure the effectiveness of policy, while introducing them to their new community. 

This course is mandatory for all MPP (including Evening Program), MIDP, and MS-DSPP students. Students working full-time are expected to take off of work in order to attend all 3 days, 9am-5pm with optional evening activities. 

McCourt Foundations is mandatory and a requirement for graduation. Any student not able to participate in all three days of Foundations will need to make up the course next year. 

Back to Top
Electives Anchor


The remaining 6 credits can come from any course offered within either the McCourt School of Public Policy or the Graduate School’s MS-DS. Students with prior coursework equivalent to core courses may be allowed to test out of or waive these courses and take electives in their place. Note that the total number of credits required for graduation does not change for students who test out of core courses.

DSPP students may take additional electives, subject to the following Graduate School rules. Graduating students may take additional credits in their final semester as long as they have a 3.5 or higher. Students will need to pay for these credits. McCourt and other graduate masters students under the Graduate School are charged per credit, regardless of how many credits they take. Please note that per the Graduate Bulletin (III D.), “Students will not be allowed to register for additional credits beyond those required for graduation for the purpose of raising an inadequate GPA.” In addition, as outlined in the Graduate Bulletin (III A. 2), students are permitted to officially audit courses, but they must register with the instructor’s permission and pay for the course. They can then switch to audit via an add/drop form, and it will appear as an AU on their transcript. We are not allowed to promote unofficial audits, but sometimes faculty will give permission to students to unofficially audit the class. They do not have to pay for the class, and it does not go on their transcript.

Please see below for a sample list of electives offered over the past academic year. This list is not exhaustive and additional courses can be found on the Registrar’s Schedule of Classes. McCourt students also have the opportunity to take electives in other Georgetown graduate programs as well as through the Consortium of Universities of the Washington Metropolitan Area. Please contact Director of Academic Affairs Nirmala Fernandes at for more information.



  • Methods including courses such as:
    • PPOL 628 Text As Data: Computational Linguistics
    • PPOL 683 Geographic Information Systems (GIS) and Applications
    • PPOL 704 Data Science Practicum
    • PPOL 760 Time Series
    • PPOL 761 Networks
    • PPOL 762 Big Data Policy
    • PPOL 740 Databases
    • PPOL 788 Public Problem Solving in the Digital Age
  • U.S. Domestic Economic Policy including courses such as:
    • PPOL 614 The Federal Budget in a Time of Madness
    • PPOL 623 National Economic Issues
    • PPOL 649 Macroeconomics
    • PPOL 758 Foreign Direct Investments in the US
    • PPOL 759 Getting People to Behave
  • International Economic Policy including courses such as:
    • PPOL 608 Asian Economic Development
    • PPOL 676 International Financial Institutions
    • PPOL 677 International Trade Policy & Negotiations
    • PPOL 734 Latin American Economic Development
  • Development Policy including courses such as:
    • PPOL 638 International Health
    • PPOL 647 International Social Development Policy
    • PPOL 681 BRICS & The Global Economy
    • PPOL 685 History and Theory of Development
    • PPOL 703 Political Economy of Foreign Aid
    • PPOL 780 Economic Complexity & Development
  • Political Strategy and Governance including courses such as:
    • PPOL 600 The Press & the Presidency
    • PPOL 612 Federalism & Intergovernmental Relations in the U.S.
    • PPOL 627 Identity Politics & Interest Groups
    • PPOL 632 Strategic Advocacy: Lobbying/Interest Groups
    • PPOL 657 Policy, Politics & the Media
  • Racial Equity and Social Justice including courses such as:
    • PPOL 499: Faith, Race & Politics
    • PPOL 624: Race & US Criminal Legal Policy
    • PPOL 719: Race & Labor Markets
    • PPOL625Urban Inequality
    • PPOL666Racial Justice in K-12 Ed Policy
    • PPOL709Identifying & Undoing Bias in Public Policy
  • Education Policy including courses such as:
    • PPOL 655 Education Productivity: Teachers & Technology Effects
    • PPOL 672 Topics: Post Secondary Education
    • PPOL 797 New Players in Education: Charter Schools
  • Environmental & Regulatory Policy including courses such as:
    • PPOL 613 Environmental and Natural Resources Economics
    • PPOL 636 Energy, Society & Politics in Developing Countries
    • PPOL 687 Nuclear Power, Climate Change, Clean Power
    • PPOL 711 Sustainable Development
  • Health Policy including courses such as:
    • PPOL 604 Health Care Quality: Recent Policy Issues
    • PPOL 642 Health Policy & Politics
    • PPOL 643 Health Care Access Demand Issues
    • PPOL 798 Politics & Policies of Addiction and Recovery
  • Homeland Security Policy including courses such as:
    • PPOL 688 Homeland Security
    • PPOL 692 Capacity Building/Counter-terrorism (previously Post Conflict Reconstruction)
    • PPOL 694 Cyber Conflict and National Security Policy
  • Management & Leadership such as:
    • PPOL 612 Federalism/Intergovernmental Relations
    • PPOL 633 Women and Leadership
    • PPOL 663 Public Leadership
    • PPOL 699 The Power & Influence of Philanthropy: Local, National, Global
    • PPOL 748 Negotiation
  • Public Management including courses such as:
    • PPOL 639 Strategic Planning & Public Policy
    • PPOL 663 Public Leadership
    • PPOL 680 Risk Management
    • PPOL 756 Contracting
    • PPOL 779 Agency Rulemaking & Adjudication: How Fed Govt Does Business
  • Social Policy including courses such as:
    • PPOL 604 Policy/Politics of Entitlements
    • PPOL 607 Child Development
    • PPOL 611 The War on Drugs: Causes, Consequences and Alternatives (formerly US Drug Policy & Its Consequences)
    • PPOL 659 Race, Faith & Politics
    • PPOL 664 Tax Policy
    • PPOL 745 U.S. Immigration Policy
Back to Top
Course Sequence Anchor

Course Sequence

A typical course sequence for MS-DSPP full-time students appears below.

Full-time MS-DSPP students complete the program in two years.


Year One: Fall Semester

  • PPOL 506 — Intermediate Microeconomics
  • PPOL 510 / PPOL 511 — Public Policy Process/Comparative Policy Process
  • PPOL 560 — Accelerated Stats for Public Policy I
  • PPOL 564 — Data Science I: Foundations

Year One: Spring Semester

  • PPOL 561 — Accelerated Stats for Public Policy II
  • PPOL 565 — Data Science II: Applied Statistical Learning
  • PPOL 568 — Data Ethics (1.5 credits)
  • PPOL 569 — Communication for Data Science (1.5 credits)

Year Two: Fall Semester

  • PPOL 563 — Data Visualization
  • PPOL 566 — Data Science III: Advanced Modeling Techniques
  • Elective

Year Two: Spring Semester

  • PPOL 514/515 — Public Management/Comparative Public Management
  • PPOL 567 — Massive Data Fundamentals (or PPOL 740 which is offered in Year Two: Fall Semester, then students can take an elective)
  • Elective
Back to Top
Data Science in Action Seminars Anchor

Data Science in Action Seminars

The Data Science for Public Policy program hosts Data Science in Action Seminars approximately once every month. These sessions allow students to directly interact with leading experts who are applying data science to important policy challenges. Experts on our schedule include:


  • Kirk Borne, Principal Data Scientist and Executive Advisor at Booz Allen Hamilton
  • Jeff Chen, Chief Innovation Officer of the U.S. Bureau of Economic Analysis
  • Matt Denny, Research Scientist at Facebook
  • Subha Madhavan, Chief Data Scientist at the Georgetown University Medical Center and Director of the Innovation Center for Biomedical Informatics
  • Graham MacDonald, Chief Data Scientist, Urban Institute
Back to Top
Summer Prep for Incoming Students Anchor

Summer Prep for Incoming Students

We’re excited for you to join the Data Science for Public Policy (DSPP) program in the fall.

Over the summer we recommend that you do preliminary work on some foundational tasks.  On this page, we list a series of resources and a list of goals.

One resource that has good “one-stop shopping” is “Computing Skills for Biologists: A ToolBox” by Allesina and Wilmes. Don’t be put-off by the mention of biology in the title – it’s a great guide for anyone doing data science.

Don’t worry, though: we will start from the beginning in all our classes.  Our sense is that even as we don’t expect you to master tools the tools ahead of time, we hope that the more exposure you have to the material ahead of time, the more comfortable you will be with the tools.

You should be able to do the following before classes start.

1)      Understand basic command line commands (Chapter 1 of Computing Skills).  You don’t need all of the material here, but should be able to do basic command line commands on your machine and understand conceptually how command line tools can be used.

2)      Understand version control with Git (Chapter 2 of Computing Skills).  You should install Git and have a sense of what is being achieved with version control.

3)      Basic Python (Chapter 3 of Computing Skills). You should install Python and be able to do basic programming tasks such as creating a loop.

4)      Basic R (Chapter 8 of Computing Skills). You should install R and RStudio and do basic programming tasks such as creating a loop.

It’s worth perusing the rest of the Computing Skills book and the other resources we list here to get a sense of some of the tools and language used in data science.  Again, do not feel like you need to master this material ahead of time, but the more you’ve got a sense of the various tools in the core toolbox, the more comfortable you’ll be.

In addition to the above, we’ve collated a list of resources that previous DSPP cohorts have found useful in the past which can be found at the link below:

Back to Top