McCourt School of Public Policy
McCourt School of Public Policy

MS-DSPP Curriculum

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.

Core Courses

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

Quantitative Social Sciences (6 credits)

Foundations of Public Policy (9 credits)

Civic Data Science (15 credits)

Ethics and Law (1.5 credits)

Communication (1.5 credits)

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:

More on McCourt’s Foundational Skill Set

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. 

Electives

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 nf168@georgetown.edu for more information.

 

SAMPLE RECENT ELECTIVE OFFERINGS

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

Year One: Spring Semester

Year Two: Fall Semester

Year Two: Spring Semester

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:

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 (ah1499@georgetown.edu).

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:

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:

MS-DSPP Resources for Incoming Students