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 5200 Accelerated Statistics for Public Policy I (3 credits)
  • PPOL 5201 Accelerated Statistics for Public Policy II (3 credits)

Foundations of Public Policy (9 credits)

  • PPOL 5004 Intermediate Microeconomics I (3 credits)
  • PPOL 5006 The Politics of Policy-Making; or PPOL 5007: Comparative Politics of Policy-Making (3 credits)
  • PPOL 5008 Public Management; or PPOL 5009: Mgmt. & Implementation in Dev. Countries (3 credits)

Civic Data Science (15 credits)

  • PPOL 5202 Data Visualization (3 credits)
  • PPOL 5203 Data Science I: Foundations (3 credits)
  • PPOL 5204 Data Science II: Applied Statistical Learning (3 credits)
  • PPOL 5205 Data Science III: Advanced Modeling Techniques (3 credits)
  • PPOL 5206 Massive Data Fundamentals (3 credits) or PPOL 740: Relational Database Sys & SQL (3 credits)

Ethics and Law (1.5 credits)

  • PPOL 5207 Data Ethics (1.5 credits)

Communication (1.5 credits)

  • PPOL 5208 Communication for Data Science (1.5 credits)
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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
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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. 

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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 Assistant Dean for Academic Affairs Nirmala Fernandes at for more information.



  • Methods including courses such as:
    • PPOL 6805: Geographic Information Systems (GIS) and Applications in Program R
    • PPOL 6809: Game Theory and Public Policy
    • PPOL 6812: Time Series
    • PPOL 6813: Political Polling Methods
    • PPOL 6841: Policy Issues: Big Data and AI
    • PPOL 6810: Relational Database Systems & SQL Programming
    • PPOL 6618: Speechwriting for Public Policy
    • PPOL 6619: Public Problem Solving in the Digital Age
  • Technology Policy including courses such as:
    • PPOL 6816: Social Network Analysis
    • PPOL 6815: Blockchain Tech for Data Science
    • PPOL 6801: Text As Data: Computational Linguistics
    • PPOL 6808: Data, Policy, & Product Mindset
    • PPOL 6707: Disruption, Innovation & Technology
    • PPOL 6812: Time Series
    • PPOL 6814: Policy Issues of Big data & AI
    • PPOL 6617: Innovation in Public Policy
  • U.S. Domestic Economic Policy including courses such as:
    • PPOL 6206: Macroeconomics
    • PPOL 6358: Poverty & The Social Safety Net
    • PPOL 6212: Antitrust & Public Policy
  • International Economic Policy including courses such as:
    • PPOL 6251: International Trade Negotiations
    • PPOL 6708: Global Hotspots
  • Development Policy including courses such as:
    • PPOL 6002: International Social Development Policy
    • PPOL 6009: Monitoring & Evaluation for Development Programs
    • PPOL 5107: Political Economy in Developing Countries
    • PPOL 6254: Global Migration Policy
    • PPOL 6012: Just Sustainability Transitions in Complex Economies
    • PPOL 6013: RBF Design For Development
  • Political Strategy and Governance including courses such as:
    • PPOL 6600: The Press & the Presidency
    • PPOL 6605: Policy, Politics & the Media
    • PPOL 6625: Modern Advocacy in a Disruptive Congress
    • PPOL 6813: Political Polling
    • PPOL 6619: Leadership & Problem Solving in the Digital Age
    • PPOL 6620: Politics Is a Contact Sport: Practical Policy Making
  • Racial Equity and Social Justice including courses such as:
    • PPOL 4901: Faith, Race & Politics
    • PPOL 6355: Race & US Criminal Legal Policy
    • PPOL 6356: Urban Inequality
    • PPOL 6300Racial Justice in K-12 Ed Policy
    • PPOL 6612: Philanthropy, Power & Impact
    • PPOL 6359Identifying & Undoing Bias in Public Policy
  • Education Policy including courses such as:
    • PPOL 6301: Education Finance Policy
    • PPOL 6302: K-12 Ed Policy Implementation
    • PPOL 6304: Current Topics in Education Policy
  • Environmental & Regulatory Policy including courses such as:
    • PPOL 6403: Natural Resources & Energy Policy
    • PPOL 5106: Sustainable Development
    • PPOL 6404: Climate Change Policy
    • PPOL 6621: Emergency Disaster Management in the US
  • Health Policy including courses such as:
    • PPOL 6351: The Policy And Politics Of Entitlements
    • PPOL 6500: Health Care Quality: Recent Policy Issues
    • PPOL 6501: Health Policy & Politics
    • PPOL 4900: Population Health: Opportunities & Challenges
  • Homeland Security Policy including courses such as:
    • PPOL 6701: Technology & National Security
    • PPOL 6702: Homeland Security
    • PPOL 6703: Capacity Building/Counter-terrorism (previously Post Conflict Reconstruction)
    • PPOL 6704: Cyber Conflict and National Security Policy
    • PPOL 6705: National Sec. Policy: Strat. & Dec. Making
  • Management & Leadership such as:
    • PPOL 6602: Federalism/Intergovernmental Relations
    • PPOL 6603: Women and Leadership
    • PPOL 5312: Public Leadership
    • PPOL 6612: Philanthropy: Power, Politics, Impact
    • PPOL 6616: Negotiation
    • PPOL 6619: Leadership and Problem Solving in the Digital Age
  • Public Management including courses such as:
    • PPOL 6604: Strategic Planning & Public Policy
    • PPOL 5312: Public Leadership
    • PPOL 6608: Risk Management
    • PPOL 6621: Emergency Disaster Management in the US
  • Social Policy including courses such as:
    • PPOL 6351: Policy/Politics of Entitlements
    • PPOL 6354: The War on Drugs: Causes, Consequences and Alternatives (formerly US Drug Policy & Its Consequences)
    • PPOL 4901: Race, Faith & Politics
    • PPOL 6207: Tax Policy
    • PPOL 6612: Philanthropy, Power & Impact
    • PPOL 6360: National Services Programs
    • PPOL 6361: Disability, Justice, Equity & Policy
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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 5004 — Intermediate Microeconomics
  • PPOL 5006 / PPOL 5007 — The Politics of Policy-Making/Comparative Politics of Policy-Making
  • PPOL 5200 — Accelerated Stats for Public Policy I
  • PPOL 5203 — Data Science I: Foundations

Year One: Spring Semester

  • PPOL 5201 — Accelerated Stats for Public Policy II
  • PPOL 5204 — Data Science II: Applied Statistical Learning
  • PPOL 5207 — Data Ethics (1.5 credits)
  • PPOL 5208 — Communication for Data Science (1.5 credits)

Year Two: Fall Semester

  • PPOL 5202 — Data Visualization
  • PPOL 5205 — Data Science III: Advanced Modeling Techniques
  • Elective

Year Two: Spring Semester

  • PPOL 5008/5009 — Public Management/Mgmt. & Implementation in Dev. Countries
  • PPOL 5206 — Massive Data Fundamentals (or PPOL 6810 which is offered in Year Two: Fall Semester, then students can take an elective)
  • Elective
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Internship Requirement Anchor

Internship Requirement

McCourt requires a formal internship experience as a program requirement for the MIDP, MPP, and MS-DSPP programs. The McCourt degrees emphasize analytical skills, enabling graduates to be highly effective in designing, analyzing and implementing policy in the US and around the globe. The internship requirement is integral to the student’s academic training at the McCourt School.

The learning objectives of the internship are:

  • Increase proficiency in specific public policy disciplines; such as management, statistics, economics, data science, politics, and/or policy-making;
  • Apply quantitative, economic, data science, and/or policy analysis concepts and theories to real-world decision-making; and
  • Develop and improve policy making skills in communication, quantitative or qualitative reasoning, data or policy analysis, and/or teamwork.

Students can intern at any time during their time at McCourt and are required to have a minimum of 120 hours of work. Students can waive the internship requirement based on prior work or internship experience. For more questions, please contact Assistant Director of Academic Affairs, Alora Hasson (

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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. Past speakers 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
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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:

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