Introduces a computational social science approach to process, analyze, and visualize urban data in a reproducible way. Modern data science toolkits to support better decision making in urban development and planning contexts will be presented. Topics covered include exploratory/statistical/agent-based urban models, network analysis, applied machine learning, and advanced data visualizations.
Prerequisite(s): Third or fourth year-status and Geography 2220A/B, or permission of the instructor.
Extra Information: 2 lecture hours, 2 lab hours.
Course Weight: 0.50
Subject Code: GEOGRAPH
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