Master of Science in Urban Analytics

The Master of Science in Urban Analytics degree is designed to give graduates a core of computing, planning, and data analysis and visualization skills to identify, analyze, and solve urban problems; to integrate those skills in an interdisciplinary way that other, single-discipline-oriented urban analytics degrees might not; and to provide depth in urban problems that can be addressed through data analytics. 

The program is interdisciplinary between the School of City and Regional Planning (SCaRP, within the College of Design), the Schools of Computational Science and Engineering and Interactive Computing (CSE and IC, both within the College of Computing), and the Stewart School of Industrial and Systems Engineering (ISyE, within the College of Engineering). Each of the four units (SCaRP, IC, CSE, and ISyE) provides expertise in a different facet of urban analytics, with interdisciplinary coordination achieved by having faculty cooperate on the development and revision of course content, especially in the core and required courses.

Urban Systems Core Courses
CP 6552Design of Smart Urban Systems3
CP 8803Special Topics in Transportation Planning (Introduction to Urban Analytics )3
Capstone and application of urban analytics in practice
CP 6960Urban Analytics Capstone Project1
CP 6962Urban Analytics Capstone Project5
Courses in spatial analysis6
Advanced Geographic Information Systems
Socioeconomic GIS
Environmental Analysis Using GIS
Transport & GIS
Courses in computational statistics6
Computational Problem Solving for Scientists and Engineers
Computing for Data Analysis: Methods and Tools
Web Search and Text Mining
Computational Data Analysis: Learning, Mining, and Computation
Computational Statistics
Theoretical Statistics
Statistical Modeling and Regression Analysis
Courses in modeling and visualization6
Intro Analytics Modeling
High Performance Computing
Data and Visual Analytics
Data Visualization: Principles and Applications
Information Visualization
Modeling and Simulation: Foundations and Implementation
Total Credit Hours30