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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.

Prerequisites

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
3.9

0.62% from Historical

Completion Rate
100%

No change from Historical

A Rate
87.76%

5.12% from Historical

Class Size
49

70.43% from Historical

Cumulative Grade Distribution

Instructors (2026 Summr)

Sorted by ratings from Rate My Professors

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