MS in Data Analytics and Policy
The Master of Science in Data Analytics and Policy prepares students to use analytics to tackle policy challenges in the public and private sectors. Students graduate with expertise in cutting-edge analytical methods relied upon by government agencies, research institutes, private companies, and nonprofit organizations. The program emphasizes the application of analytics to substantive issues to develop students into data-driven leaders.
The schedule for completing this 12-course degree program is flexible. Many students work full time while attending the program on a part-time basis and complete their degree in two years. Full-time students can complete the degree more quickly. The MS in Data Analytics and Policy is offered primarily online, although some courses may be offered onsite in Washington, D.C.
Students may choose to earn a concentration within one of the following specialized areas: political behavior and policy analysis, geospatial analysis, statistical analysis, or public management. The electives cover a wide range of analytical methods, including machine learning, predictive analysis, text analysis, database management systems, computational modeling, civic technology, economic analysis, survey methodology, risk analysis, and data privacy.
Admissions Criteria for all Advanced Academic Programs
PROGRAM-SPECIFIC REQUIREMENTS
In addition to the materials and credentials required for all programs, the Master of Science in Data Analytics and Policy requires:
- Current resume or academic CV
- Statement of purpose: An approximately 500-word statement that explains your reasons for seeking admission and describes how earning the degree will advance your career in data analytics and/or public policy. Your statement should describe your ability or potential to perform quantitative analyses.
- Writing sample: A 1,250- to 1,750-word writing sample that demonstrates your ability to make and support an argument. Writing samples written within the last five years are preferred. Writing samples may not be co-authored. If you do not have an appropriate academic or professional sample on hand, you may respond to the following prompt: “Describe a current policy challenge and explain what should be done to address it.”
- Two letters of recommendation: Please provide contact information for two recommenders. Recommenders should be previous academic instructors or professional colleagues who can evaluate your academic and professional accomplishments and suitability for graduate study. When possible, recommenders should provide their letters on institutional or business letterhead. It is preferred that students who have earned their bachelor’s degree within the last three years provide at least one reference from a faculty member from their undergraduate institution.
Program Requirements
- Five required core courses
- Seven elective courses
Core Courses
The five required core courses provide the foundations for conducting and presenting the results of quantitative data analysis.
| Code | Title | Credits |
|---|---|---|
| Core Courses - Required | ||
| AS.470.681 | Probability and Statistics | 3 |
| AS.470.768 | Programming and Data Management | 3 |
| AS.470.709 | Quantitative Methods | 3 |
| AS.470.673 | Data Visualization | 3 |
| AS.470.862 | Capstone for Data Analytics and Policy | 3 |
Electives and Concentrations
Students will complete seven elective courses for the MS in Data Analytics and Policy, in addition to required core courses.
There are four concentrations offered through the MS in Data Analytics and Policy. Pursuing a concentration is optional. To earn a concentration, four of the student’s electives must be in the concentration area.
All courses from the concentrations on this page may count as one of the seven elective courses, unless specifically noted otherwise.
Concentration in Statistical Analysis
| Code | Title | Credits |
|---|---|---|
| AS.470.624 | Healthcare Analytics and Policy | 3 |
| AS.470.643 | Text as Data | 3 |
| AS.470.667 | Machine Learning Methods and Applications | 3 |
| AS.470.669 | Math for Data Scientists | 3 |
| AS.470.694 | Big Data Management Systems | 3 |
| AS.470.699 | Applied Performance Analytics | 3 |
| AS.470.700 | Cloud Computing in the Public Sector | 3 |
| AS.470.703 | Urban Data Analytics | 3 |
| AS.470.708 | Unleashing Open Data with Python | 3 |
| AS.470.743 | Data Mining and Predictive Analytics | 3 |
| AS.470.758 | Data-Driven Campaigns and Elections | 3 |
| AS.470.763 | Database Management Systems | 3 |
| AS.470.764 | Survey Methodology | 3 |
| AS.470.769 | Data Science for Public Policy | 3 |
| AS.470.779 | Computational Modeling for Policy and Security Analysis | 3 |
| AS.420.677 | Spatial Statistics (Not available as a general elective outside of the concentration) | 3 |
Concentration in Public Management
| Code | Title | Credits |
|---|---|---|
| AS.470.605 | Global Political Economy | 3 |
| AS.470.608 | Public Policy Evaluation & the Policy Process | 3 |
| AS.470.627 | Financial Management & Analysis in the Public Sector | 3 |
| AS.470.631 | Economics for Public Decision-Making | 3 |
| AS.470.645 | The Budgetary Process | 3 |
| AS.470.662 | Expertise and Evidence in Policymaking | 3 |
| AS.470.671 | Risk Management Analytics | 3 |
| AS.470.694 | Big Data Management Systems | 3 |
| AS.470.731 | Privacy in a Data-driven Society | 3 |
| AS.470.763 | Database Management Systems | 3 |
| AS.470.798 | Financial Management and Analysis in Nonprofits | 3 |
Concentration in political Behavior and Policy Analysis
| Code | Title | Credits |
|---|---|---|
| AS.470.608 | Public Policy Evaluation & the Policy Process | 3 |
| AS.470.620 | Race, Politics, and Policy | 3 |
| AS.470.624 | Healthcare Analytics and Policy | 3 |
| AS.470.636 | Cognitive and Behavioral Foundations for Artificial Intelligence | 3 |
| AS.470.641 | Introduction to Advocacy and Lobbying | 3 |
| AS.470.662 | Expertise and Evidence in Policymaking | 3 |
| AS.470.688 | Political Institutions and the Policy Process | 3 |
| AS.470.699 | Applied Performance Analytics | 3 |
| AS.470.703 | Urban Data Analytics | 3 |
| AS.470.733 | Origins and Influence of Public Opinion on American Democracy and Elections | 3 |
| AS.470.745 | Terrorist Financing Analysis and Counterterrorist Finance Techniques | 3 |
| AS.470.758 | Data-Driven Campaigns and Elections | 3 |
| AS.470.769 | Data Science for Public Policy | 3 |
| AS.470.779 | Computational Modeling for Policy and Security Analysis | 3 |
| AS.470.835 | DC Lab: Politics, Policy, and Analytics | 3 |
| AS.473.602 | Intelligence Analysis | 3 |
| AS.473.663 | The Intelligence-Policy Nexus | 3 |
Concentration in Geospatial Analysis
| Code | Title | Credits |
|---|---|---|
| AS.472.611 | Analyzing Social Media and Geospatial Information | 3 |
| AS.472.612 | Geospatial Analysis: Communicating with Multiple Audiences | 3 |
| AS.430.600 | Web GIS | 4 |
| AS.430.601 | Geographic Information Systems (GIS) | 4 |
| AS.430.604 | Spatial Analytics | 4 |
| AS.430.606 | Programming in GIS | 4 |
| AS.430.602 | Remote Sensing: Systems and Applications (Not available as a general elective outside of the concentration) | 4 |
| AS.430.605 | Development and Management of GIS Projects (Not available as a general elective outside of the concentration) | 4 |
| AS.430.607 | Spatial Databases and Data Interoperability (Not available as a general elective outside of the concentration) | 4 |
| AS.430.608 | GIS and Spatial Decision Support Systems (Not available as a general elective outside of the concentration) | 4 |
| AS.430.609 | Spatial Data Management: Quality and Control (Not available as a general elective outside of the concentration) | 4 |
| AS.430.610 | GIS for Infrastructure Management (Not available as a general elective outside of the concentration) | 4 |
| AS.430.611 | Geospatial Ontologies and Semantics (Not available as a general elective outside of the concentration) | 4 |
| AS.430.612 | Cartographic Design and Visualization (Not available as a general elective outside of the concentration) | 4 |
| AS.430.613 | Advanced Topics in Remote Sensing (Not available as a general elective outside of the concentration) | 4 |
| AS.430.615 | Big Data Analytics: Tools and Techniques (Not available as a general elective outside of the concentration) | 4 |
| AS.430.617 | Census Data Mining: Visualization and Analytics (Not available as a general elective outside of the concentration) | 4 |
| AS.430.618 | Advanced Python Scripting for GIS (Not available as a general elective outside of the concentration) | 4 |
| AS.430.619 | Web Application Development (Not available as a general elective outside of the concentration) | 4 |
| AS.430.621 | GIS for Emergency Management (Not available as a general elective outside of the concentration) | 4 |
| AS.430.623 | Geo Apps (Not available as a general elective outside of the concentration) | 4 |
| AS.430.625 | System Architecture for Enterprise GIS (Not available as a general elective outside of the concentration) | 4 |
| AS.430.627 | Artificial Intelligence and Machine Learning in Geospatial Technology (Not available as a general elective outside of the concentration) | 4 |
| AS.430.629 | Drones in Geospatial Decision Making (Not available as a general elective outside of the concentration) | 4 |
| AS.430.631 | Spatial Algorithms and Data Structures (Not available as a general elective outside of the concentration) | 4 |
| AS.430.633 | Advanced Spatio-Temporal Statistics (Not available as a general elective outside of the concentration) | 4 |
| AS.430.635 | Urban Analytics (Not available as a general elective outside of the concentration) | 4 |