Data Analytics and Policy, Master of Science | Johns Hopkins University Academic Catalogue

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 program includes six required core courses and four electives. The electives cover a wide range of analytical methods, including machine learning, predictive analytics, text analysis, spatial analytics (GIS), economic analysis, survey methodology, and policy analysis.

The schedule for completing this 10-course degree program is flexible. 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.

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 program requires:

1. Resume or Academic CV

2. Two letters of recommendation

3. Statement of Purpose: A statement, up to one page in length, should be provided, describing the applicant's personal background and/or a part of their life experience that has shaped their goals. This may include elaboration on personal challenges and opportunities that have influenced the decision to pursue a graduate degree at Johns Hopkins.

4. Writing Sample: Applicants should submit a four to six page writing sample (double spaced preferred). Writing samples may not be co-authored. There are two options, both of which are acceptable:

Applicants with experience doing data analysis should submit a sample that demonstrates their ability to use data to answer research questions, address policy problems, or support data-driven decision-making. This could be a class paper or an example from work experience.
Applicants with limited background in data analysis may describe their interest in learning to use data analytic methods and how they intend to apply these tools to an area of interest in policy or politics.

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.
Four elective courses that cover additional topics in data analysis, public policy, and politics.

Course List
Code	Title	Credits
Six Core Courses - Required		18
AS.470.681	Introduction to Data Analytics and Policy (previously titled Probability and Statistics)
AS.470.768	Programming and Data Management
AS.470.673	Data Visualization
AS.470.709	Quantitative Methods for Policy and Political Analysis (previously titled Quantitative Methods)
AS.470.667	Machine Learning Methods and Applications
AS.470.862	Capstone for Data Analytics and Policy
Four Electives		12 -14
Total Credits		30-32

Electives

Course List
Code	Title	Credits
AS.470.605	Global Political Economy	3
AS.470.608	Public Policy Evaluation & the Policy Process	3
AS.470.617	The Courts and Public Policy	3
AS.470.620	Race, Politics, and Policy	3
AS.470.627	Financial Management & Analysis in the Public Sector	3
AS.470.631	Economics for Public Decision-Making	3
AS.470.641	Introduction to Advocacy and Lobbying	3
AS.470.643	Text as Data	3
AS.470.645	The Budgetary Process	3
AS.470.662	Expertise and Evidence in Policymaking	3
AS.470.669	Math for Data Scientists	3
AS.470.703	Urban Data Analytics	3
AS.470.738	AI Technology, Innovation, and Policy	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.470.781	Cloud Computing in the Public Sector	3
AS.470.684	Legislative Language and Policymaking	3
AS.470.688	Political Institutions and the Policy Process	3
AS.470.701	Congress: Why the First Branch Matters	3
AS.470.798	Financial Management and Analysis in Nonprofits	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
AS.472.612	Geospatial Analysis: Communicating with Multiple Audiences	3
AS.430.600	Web GIS	3
AS.430.601	Geographic Information Systems (GIS)	3
AS.430.602	Remote Sensing: Systems and Applications	3
AS.430.603	Geospatial Statistics	3
AS.430.604	Spatial Analytics	4
AS.430.606	Programming in GIS	4
AS.430.607	Spatial Databases and Data Interoperability	3
AS.430.609	Spatial Data Management: Quality and Control	3
AS.430.610	GIS for Infrastructure Management	3
AS.430.612	Cartographic Design and Visualization	3
AS.430.615	Big Data Analytics: Tools and Techniques	3
AS.430.617	Census Data Mining: Visualization and Analytics	3
AS.430.619	Web Application Development	3
AS.430.621	GIS for Emergency Management	3
AS.430.627	Artificial Intelligence and Machine Learning in Geospatial Technology	3
AS.430.629	Drones in Geospatial Decision Making	3
AS.430.631	Spatial Algorithms and Data Structures	3
AS.430.635	Urban Analytics	3