Admission into the Data Science graduate program
Select three courses to fulfill the pathway requirement.
ECON 600: Policy Consequences of Economic Analysis
A course in political economy dealing with the implications and consequences for policy outcomes of different models of economic analysis, including an introduction to microeconomic theory. Note: May not be counted toward the concentration in economics.
PUBL 601: Political and Social Context of the Policymaking Process
This course is designed to introduce students to the processes by which policy is made in the United States. It introduces students to the policymaking system, including the institutional, structural and political contexts, as well as the policy making environment. The various stages of the policymaking process from problem definition and agenda-setting to implementation are examined and discussed, and important theories and models of policy making are presented. Significant concepts relating to the political analysis of public policy are discussed, such as the social construction of problems, group demands, political influence and resources, motivations and incentive for political behavior and political feasibility.
PUBL 603: Theory and Practice of Policy Analysis
An overview of the basic principles and elements of policy analysis. The course focuses on the activities and elements of policy analysts. In addition, the relationship between policy analysis and policy making, along with emerging professional and ethical issues, are addressed.
PUBL 607: Statistical Applications in Evaluation Research
Advanced course in analyzing and evaluating data. Focuses on interpreting statistical procedures for assessing the impact of programs and policies based on a variety of experimental and quasi-experimental designs, including true experiments, non-equivalent control group designs and interrupted time-series designs.
PUBL 608: Applied Multivariate Regression Analysis
An introduction to the practical application of widely used basic multivariate regression techniques. Experience in the use of these techniques is provided through hands-on exercises and the preparation of an original regression analysis of real-world data in an area of interest selected by the student. Methods covered include multiple linear regression, models with binary dependent variables, analysis of pooled data, and methods for assessing and comparing the performance of alternative models. Rather than focusing on the mechanics of regression computation, the course emphasizes the basic concepts involved in constructing and estimating regression models, and in interpreting their results. Consent of instructor.
PUBL 610: Special Topics In Public Policy
Topics selected on the basis of the background and interests of the faculty member and students.
Consult with Graduate Program Director to determine which courses align with your professional goals.
The growing integration of data science with public policy drives job growth in this field. According to Labor Insight, an employer-demand tool, there is a very high demand for these positions in the Washington DC and Baltimore metropolitan area. Possible job titles for program graduates include Policy Analyst, Program Analyst, and Economist. Our recent graduates work for a wide range of industrial organizations and government agencies.
Download the Academic Planning Form as unofficial guidance in planning your Data Science Master’s program.
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