Master of Science in Civic Analytics (MSCA)
Introduction
The Master of Science in Civic Analytics is a first of its kind degree that combines study in civic technology and data analytics for those in the government and nonprofit sectors. The curriculum provides a strong foundation in the areas of applied statistics, geospatial applications, and data visualization, but balanced with traditional core subjects in public affairs. The program is designed to develop a substantial capacity for students to solve complex public problems with information technology. Graduates will have skills that will be highly desirable in many employer contexts, including information offices in city, state and federal agencies; large nonprofits; technology consulting firms, and government contractors. The program is also committed to finding ethical solutions to problems and reflect public values.
The MSCA program is suitable for individuals with a diverse array of baccalaureate degrees, including those with backgrounds in public policy, political science, statistics, information technology, geography, mathematics, computer science, and economics. Students can take advantage of the expertise contained within the college’s nationally prominent research centers, including the Urban Data Visualization Laboratory, the Network Governance Laboratory, and the Urban Transportation Center. The program also works to integrate students into the city’s civic tech community, helping to provide a valuable form of service-learning while also acquiring skills from field-leading practitioners in civic technology.
Admissions
Degree Required: Bachelor’s degree
Baccalaureate Field: Baccalaureate degree holders in any field are eligible for admission to the program.
Grade Point Average: Minimum 2.75 out of 4.00 for the final 60 semester (90 quarter) hours of undergraduate study. Applicants with a master’s degree must have maintained a GPA of at least 2.75 out of 4.00 in previous work. Applicants with GPAs below 2.75 are considered for limited standing admission.
Letters of Recommendation & Writing Sample (OPTIONAL): Applicants may submit a 5–10 page writing sample and up to three letters of recommendation. These letters should be from instructors familiar with the applicant’s academic training or supervisor familiar with the applicant’s professional experiences.
Personal Statement: Required. The personal statement shall address how the MSCA degree will further the student’s educational and career objectives. The student will also discuss relevant prior coursework or professional experience, and willingness to learn information technology and statistics.
Resume Required. Applicants must submit an updated resume with their application.
Other Requirements (Prerequisites): The student must provide documentation that they have completed an undergraduate or graduate-level data analysis or statistics course in the last three years with a grade of B or higher. This course will be more than a research design course and must cover descriptive and inferential statistics, including regression. If the student does not have such a course but meets the other requirements for admission, they will be required to enroll in PA 402 Principles of Data Analysis or equivalent course.
Degree Requirements
Requirements for MSCA as of Spring 2025 – the Graduate Catalog will always have the most updated curriculum available.
FOUNDATIONAL CORE (25 HOURS)
PA 401: Foundations of Public Service
PA 402: Intro to Data Management and Analysis
PA 403: Economics for Management and Policy
PA 506: Public Policy Development and Process
PA 521: Strategic Management
PA 590: Capstone for Public Policy, Management, and Analytics
PA 591: Managing your Career (1 hour)
MSCA CORE (20 HOURS)
PA 431: Civic Technology
PA 434: Intermediate Data Management and Analysis
PA 446: Coding for Civic Data Applications
PA 470: AI and Machine Learning
PA 541: Advanced Data Analysis I
MSCA ELECTIVES (8 HOURS)*
*Pre-approved MSCA Electives:
PA 528 (4): Public Program Evaluation
PA 542 (4): Advanced Data Analysis II
PA 543 (4): Social Network Analysis
PA 544 (4): Qualitative Research Methods in Public Administration
PA 582 (4): Survey Data Collection Methods: Theory and Practice
UPP 462 (4): Intermediate GIS for Planning and Policy
UPP 463 (4): Complexity-Based Models for Planning and Policy
UPP 464 (4): Advanced Visualization Techniques
IDS 509 (4): Data and Prescriptive Analytics
IDS 576 (4): Deep Learning and Modern Applications
IDS 572 (4): Data Mining for Business
IDS 576 (4): Advanced Predictive Models
EPSY 550 (4): Rating Scale and Questionnaire Design and Analysis
EPSY 551 (4): Item Response Theory/Rasch Measurement
EPSY 584 (4): Hierarchical Linear Models
EPSY 585 (4): Non-Parametric Modeling
EPSY 587 (4): Structural Equation Modeling
BSTT 426 (3): Health Data Analytics Using Python Programming
BSTT 537 (3): Longitudinal Data Analysis
Failure to Progress Statement
- For programs (MPA/MPP/MSCA) requiring 41 to 64 semester hours of graduate work, the time limit is six consecutive calendar years. Students pursuing more than one degree at the same time will be given an additional two years. Students who do not graduate by these deadlines will be dismissed from the program for failure to progress. Time spent on a leave of absence approved by the program and the Graduate College is not counted toward the degree time limit.
Advisors:
Megan Daly
Academic Advisor
Public Policy, Management, and Analytics (M/C 278)
ppma@uic.edu