Program Overview

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.

Program Overview

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 program is offered primarily online and can be completed as a fully online program. Students in the Washington, D.C. area may have an opportunity to take some elective courses on campus.

Admission Criteria

In addition to the materials and credentials required for all programs, the Master of Science in Data Analytics and Policy program requires:

• A resume or academic CV
• Two letters of recommendation
• A statement of purpose, up to one page in length, describing the applicant's personal background and/or a part of their life experience that has shaped their goals
• A writing sample of approximately 1,250 words, demonstrating the applicant's ability to use quantitative data to answer research questions, address policy problems, or support data-driven decision-making

Program Requirements

To earn the MS in Data Analytics and Policy, students must complete:

• Six required core courses that provide the foundations for conducting and presenting the results of quantitative data analysis
• Six elective courses that cover additional topics in data analysis, public policy, and politics

Core Courses

The six core courses are:

1. AS.470.681: Introduction to Data Analytics and Policy
2. AS.470.768: Programming and Data Management
3. AS.470.673: Data Visualization
4. AS.470.709: Quantitative Methods for Policy and Political Analysis
5. AS.470.667: Machine Learning Methods and Applications
6. AS.470.862: Capstone for Data Analytics and Policy

Electives and Concentrations

Students will complete six elective courses for the MS in Data Analytics and Policy, in addition to the six required core courses, for a total of 12 courses to complete the degree. Students may choose to earn a concentration in one of the following specialized elective areas: statistical analysis, public management, political behavior and policy analysis, or geospatial analysis.

Concentration in Statistical Analysis

Courses for this concentration include:

• AS.470.643: Text as Data
• AS.470.662: Expertise and Evidence in Policymaking
• AS.470.669: Math for Data Scientists
• AS.470.703: Urban Data Analytics
• AS.470.708: Unleashing Open Data with Python
• AS.470.738: AI Technology, Innovation, and Policy
• AS.470.758: Data-Driven Campaigns and Elections
• AS.470.763: Database Management Systems
• AS.470.764: Survey Methodology
• AS.470.769: Data Science for Public Policy
• AS.470.781: Cloud Computing in the Public Sector

Concentration in Public Management

Courses for this concentration include:

• AS.470.605: Global Political Economy
• AS.470.608: Public Policy Evaluation & the Policy Process
• AS.470.627: Financial Management & Analysis in the Public Sector
• AS.470.631: Economics for Public Decision-Making
• AS.470.645: The Budgetary Process
• AS.470.662: Expertise and Evidence in Policymaking
• AS.470.671: Risk Management Analytics
• AS.470.738: AI Technology, Innovation, and Policy
• AS.470.781: Cloud Computing in the Public Sector
• AS.470.798: Financial Management and Analysis in Nonprofits

Concentration in Political Behavior and Policy Analysis

Courses for this concentration include:

• AS.470.608: Public Policy Evaluation & the Policy Process
• AS.470.617: The Courts and Public Policy
• AS.470.620: Race, Politics, and Policy
• AS.470.641: Introduction to Advocacy and Lobbying
• AS.470.662: Expertise and Evidence in Policymaking
• AS.470.684: Legislative Language and Policymaking
• AS.470.688: Political Institutions and the Policy Process
• AS.470.701: Congress: Why the First Branch Matters
• AS.470.703: Urban Data Analytics
• AS.470.738: AI Technology, Innovation, and Policy
• AS.470.758: Data-Driven Campaigns and Elections
• AS.470.769: Data Science for Public Policy
• AS.470.835: DC Lab: Politics, Policy, and Analytics
• AS.473.602: Intelligence Analysis
• AS.473.663: The Intelligence-Policy Nexus

Concentration in Geospatial Analysis

Courses for this concentration include:

• AS.472.611: Analyzing Social Media and Geospatial Information
• AS.472.612: Geospatial Analysis: Communicating with Multiple Audiences
• AS.430.600: Web GIS
• AS.430.601: Geographic Information Systems (GIS)
• AS.430.602: Remote Sensing: Systems and Applications
• AS.430.603: Geospatial Statistics
• AS.430.604: Spatial Analytics
• AS.430.606: Programming in GIS
• AS.430.607: Spatial Databases and Data Interoperability
• AS.430.609: Spatial Data Management: Quality and Control
• AS.430.610: GIS for Infrastructure Management
• AS.430.612: Cartographic Design and Visualization
• AS.430.615: Big Data Analytics: Tools and Techniques
• AS.430.617: Census Data Mining: Visualization and Analytics
• AS.430.619: Web Application Development
• AS.430.621: GIS for Emergency Management
• AS.430.627: Artificial Intelligence and Machine Learning in Geospatial Technology
• AS.430.629: Drones in Geospatial Decision Making
• AS.430.631: Spatial Algorithms and Data Structures
• AS.430.635: Urban Analytics