This course introduces a broad spectrum of theories, conceptual models, machine learning, and computational modeling that are used in and related to geospatial and social data. Course contents include discussions of, and hands-on exercise with, geo-social data analytics, map-based visualization, community dynamics models, smart cities theories, and GIS-based system development. This course aims to help students grow as IT professionals who can (1) understand critical issues in smart and connected communities (S&CC), (2) combine data-driven approaches in understanding and addressing the problems, and (3) communicate the geographically-embedded social patterns based on data analysis results through visualizations and interactive systems.Offered by Info Sciences & Technology. May not be repeated for credit.
Geo-data Analytics & Theory
George Mason University
AIT 722 002 - CRN 83675
Times and Days
Programming (Python or R); Statistics