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148-0015-00L 1 Credits WBZ D-BAUG
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Geo.BigData(Science)

Lecturers & Examiners: Prof. Dr. Lorenz Hurni, Prof. Dr. Martin Raubal
VVZ CR n/a

Last Updated: 2026-02-05 16:37:59

Abstract

This module examines the significance of the mega trends: Big Data, Machine Learning, Linked Open Data and Internet of Things. It shows how geodata can be stored in big data infrastructures and analyzed using machine learning without having to do without GIS tools such as QGIS. It also highlights the potential of linked open data, IoT and artificial intelligence for geoinformatics.

General Information

Language
German
Levels
WBZ
Frequency
Yearly recurring

Examination

Type
ungraded semester performance

Registration & Places

Priority: Registration for the course unit is only possible for the primary target group

Course Components

Type Title Time & Place Hours
lecture with exercise Geo.BigData(Science)
Blockkurs 25. – 27. März 2024, HIL G 21 (Montag/Dienstag 8.45 bis 16.45 Uhr, Mittwoch 8.45 bis 12.15 Uhr)
  • 25.03. - 26.03 Date 08:50-16:30 (HIL G 21)
  • 27.03 Date 08:50-12:30 (HIL G 21)
24 h semesterly

Offered In