GIS and Spatial Data Science

This course teaches the foundations of spatial data science, the analysis of patterns tied to physical locations such as neighborhoods, Census tracts, or transit routes.

How can these data be transformed to human expressions and narratives that are utilized in planning? The course begins with an introduction to various data science tools and reviews the basics of programming with Python.

Then, specific Python libraries for spatial analysis and advanced geoprocessing are introduced.

All lessons utilize real data with analytical methods, visualizing relevant and contemporary urban phenomena such as equitable access to public transit, land use and population density, walkability scores, crime mapping, and policy solutions according to demographic and socio-economic vulnerabilities and needs, among other.

At the conclusion of this course, students will be able to critically describe, analyze, and visualize spatial data for planning practices and research.

No prior programming experience is required.

The live courses, asynchronous recordings, and myriad resources on the course site will assist you in ensuring you have a successful, fun experience learning geospatial analyses with various Python libraries.