After successful completion of the course, students are able to...

• Methoden zur raumbezogenen Datenanalyse anzuwenden
• häufige Fehlerquellen bei der Analyse zu erkennen
• Muster aus Daten zu extrahieren
• Algorithmen für Netzwerkanalyse und räumliche Optimierung anzuwenden
• maschinelle Verfahren anzuwenden (Machine Learning)
• Standortanalysen durchzuführen
• praktische Kenntnisse in der Anwendung entsprechender Tools vertiefen

Explanation of concepts and practical exercises to understand these concepts:

• Geodatenanalyse
• Räumliche Statistik
• Raumzeitliche Analysen
• Netzwerkanalyse 
• Spatial Data Mining
• Machine Learning
• Clustering 
• Optimierung 
• Standortoptimierung

The theoretical concepts are presented and discussed on the basis of slides and scientific literature. Practical tasks are carried out in the laboratory on the basis of these concepts.

The lectures and lab sessions will be held in presence. Upon prior notice, individual sessions can be held in distance learning mode if required by the circumstances.

- Mini quizzes. At least 50% of the points must be achieved

- Written exam  (closed book). At least 50% of the points must be achieved

Grade: 20% miniquizzes + 80% written exam