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Master of Science in Applied Political Analytics 


The Master of Science in Applied Political Analytics is offered jointly through the Department of Government and Politics and the Joint Program in Survey Methodology in the College of Behavioral and Social Sciences. The program provides an opportunity for students to apply acquired core skills to address real-world problems.

Mentoring and advising are an essential part of the program. Students meet with faculty and the academic program director to ensure that educational goals and career learning and development goals are met. Students should contact the program director, Dr. Candace M. Turitto, via email: political-analytics@umd.edu.

Overview

The Master of Science in Applied Political Analytics (APAN) is a 36-credit, 12-course graduate program that provides advanced training in the application of data science to the analysis of key issues in political science. Plan of study includes 18 credits (six 3-credit courses) in political science and 18 credits (six 3-credit courses) in data science. 

  • Addresses the unique challenges in developing and working with social and behavioral data in measurement design, data collection, ethics and governance, communication, data management, modeling, and analysis. 
  • Develops a firm foundation in theoretical and empirical research to communicate effectively and adapt easily to new questions and issues. 
  • Equips aspiring professionals with the foundations of political science and training in the principles and practices of survey research, enabling students to delve more deeply into the technical aspects of data collection, survey methods, and statistical modeling.
  • Students complete a major project in one of their courses that provides the opportunity to apply acquired core skills to address real-world problems.
  • Offers two plans of study: Comprehensive Option or 4+1 Option.

Program Features

Equips students with two different sets of skills. This graduate training allows students to stand out in a growing, but crowded, job market for political analysts. 

  • The first skill set offers a solid technical background to work with data sets of an order of magnitude unimaginable to previous generations. Data driven strategies are key to success when planning messaging or providing needed services. 
  • The second skill set provides a rich background in political science to apply meaningful analytical skills to important policy questions and issues.

Guidelines

The Comprehensive Option includes 18 credits in the first year of study and 18 credits in the second year of study.

  • Can be completed in eighteen months of continuous full-time enrollment. See Designation of Full-time/Part-time Status.
  • Designed for working professionals, students can earn a University of Maryland degree while continuing to work full-time with minimal disruption to personal and professional life.
  • Students assessed program tuition for all courses.

Registration Overview

  • See the sample plan of study, below. Students should use this as a guide to develop a plan with the academic program director. 
  • Actual course offerings are determined by the program and may vary semester to semester. Students should note if a course has a pre-requisite or co-requisite. 
  • Specific class meeting information (days and time) is posted on UMD’s interactive web service services, Testudo. Once on that site, select “Schedule of Classes,” then the term/year. Courses are listed by academic unit. 
  • The program uses specific section codes for registration, which are listed on the sample plan of study.

Comprehensive Option: Full-time, Sample Plan 

Semester Year Course Number Campus Section Online Section Credits
Fall 1 GVPT601 PCA* PWA* 3
Fall 1 SURV615 PCA* PWA* 3
Fall 1 GVPT628 PCA* PWA* 3
Spring 1 GVPT624 PCA* PWA* 3
Spring 1 SURV630 PCA* PWA* 3
Spring 1 SURV616 PCA* PWA* 3
Fall 2 GVPT635 PCA* PWA* 3
Fall 2 SURV727 PCA* PWA* 3
Fall 2 SURV740 PCA* PWA* 3
Winter 2 GVPT728 n/a PWA* 3
Spring 2 GVPT685 PCA* PWA* 3
Spring 2 GVPT715 PCA* PWA* 3

Guidelines 

  • University of Maryland degree-seeking undergraduate students complete 9 credits in their senior year and 27 credits in nine months of continuous full-time enrollment as a graduate student. See Designation of Full-time/Part-time Status
  • In their junior year, students must first apply and be admitted into the undergraduate portion of the 4+1 option. Students then complete 9 program credits in their senior year as part of the undergraduate degree.
  • Early in the spring semester of their senior year, students formally apply to The Graduate School. Upon admission, students complete the master’s degree by enrolling in the remaining 27 credits. Courses taken in the student’s senior year count towards both the undergraduate and master’s degree. 
  • UMD undergraduates are assessed tuition at their regular undergraduate rate for the 9 credits taken in their senior year and assessed the program tuition rate for the remaining 27 credits.

Eligibility 

The 4+1 option is open to UMD degree-seeking undergraduate majors with a 3.0 or Higher GPA.

Registration Overview

  • See the sample plan of study, below. Students should use this as a guide to develop a plan with the academic program director. 
  • Actual course offerings are determined by the program and may vary semester to semester. Students should note if a course has a pre-requisite or co-requisite. 
  • Specific class meeting information (days and time) is posted on UMD’s interactive web service services, Testudo. Once on that site, select “Schedule of Classes,” then the term/year. Courses are listed by academic unit. 
  • The program uses specific section codes for registration, which are listed on the sample plan of study.

4+1 Option: Full-time, Sample Plan 

Semester Year Course Number Campus Section Online Section Credits
Fall Senior GVPT601 4+1 Option 4+1 Option 3
Fall Senior GVPT628 4+1 Option 4+1 Option 3
Spring Senior SURV630 4+1 Option 4+1 Option 3
Fall 5 GVPT635 PCA* PWA* 3
Fall 5 SURV615 PCA* PWA* 3
Fall 5 SURV727 PCA* PWA* 3
Fall 5 SURV740 PCA* PWA* 3
Winter 5 GVPT728 n/a PWA* 3
Spring 5 GVPT624 PCA* PWA* 3
Spring 5 GVPT685 PCA* PWA* 3
Spring 5 SURV616 PCA* PWA* 3
Spring 5 GVPT715 PCA* PWA* 3

For a listing of program courses, see the Graduate School Catalog program requirements for APAN. For course descriptions that includes pre-requisites or co-requisites, see GVPT and SURV.

Overall

  • Features dynamic and interactive seminar-style in-person learning, supplemented with online instruction. 
  • Uses the semester academic calendar with classes held in fall and spring semester (16 weeks each) and winter session (3-weeks).
  • Instruction provided by University of Maryland faculty and professionals in the field. 

In-Person Learning

  • Most courses offered via in-person learning.
  • Classes meet in UMD College Park campus classrooms, offering a focused, distraction-free learning environment. 
  • Students enrolled in a program that features in-person instruction are required to submit the University’s Immunization Record Form prior to the first day of their first semester/term. See Health Requirements

Online Learning

  • Using advanced audio and video technology, UMD’s online learning environment delivers dynamic and interactive content.
  • Featuring convenience and flexibility, online instruction permits asynchronous or synchronous participation.
  • Lectures are video archived. Students who are unable to attend in real time can review the session through asynchronous participation.

Upon successful completion, graduates will have mastered the following competencies:

  • Provide a more rigorous theoretical background in at least one major sub-field in political science.
  • Enhance a student’s existing understanding of political analysis (from undergraduate coursework) with a rigorous introduction to additional analytical tools.
  • Provide a venue for student to practice theoretically rigorous political analysis with their expanded tool set.
  • Provide a rigorous understanding of the fundamentals of data science.
  • Introduce students to the key tools of “Big Data” collection, management, and analysis.
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