ADVANCED GEOCOMPUTING AND GEOSPATIAL BIG DATA ANALYTICS

GEOG 573

Course Description

Geospatial big data is an extension of big data with an emphasis on the geospatial component. It is used to describe large volumes of georeferenced data about various aspects of the environment and society captured by millions of environmental and human sensors. An introduction to the theory, techniques, and analytical methods for geospatial big data. Methods for storing, processing, analyzing, and visualizing various types of geospatial big data using advanced Python programming will be introduced. Designed for students who have programming experience and want to reinforce their programming skills and learn AI and machine learning methods for solving geospatial big data problems.

Prerequisties

GEOG 378 , COMPSCI 220 , or graduate/professional standing

Satisfies

This course does not satisfy any prerequisites.

Credits

Not Reported

Offered

Not Reported

Grade Point Average

3.87

0.39% from Historical

Completion Rate

100%

No change from Historical

A Rate

80.65%

0.43% from Historical

Class Size

40.91% from Historical

Instructors (2025 Fall)

Sorted by ratings from Rate My Professors

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