EECS 397, 497: Spatial Data Science and Spatial Computing

Quarter Offered

Fall : WF 1-2:20 ; Hecht


Tom Erickson, a well-known researcher at IBM, has said that in the near future, he expects maps to be as important to the computing experience as the GUI is today. At the same time, more and more data science projects require knowledge of the unique properties of spatial data and the special tools for processing spatial data. This course will provide students with the necessary theory and applied knowledge to succeed in an increasingly "geo" world of computer science and data science. The course will have a major group project component. For students interested in the job market, the project will involve either (1) conception and/or development of a location-aware technology (e.g. app) that they can add to their portfolio or (2) a spatial data science project with a commercial bent. For those in or interested in graduate school, the project will consist of the conception and early execution of a spatial computing or spatial data science research project.