Teaching Winter Term 2021 / 2022

Welcome to the teaching page for winter term 2021 / 2022. Here you find all resources and information.

• Research Seminar
  In this seminar, the master and PhD candidates get into touch with diverse problems, research results and techniques from the field of research of the chair. The objective of this seminar is to improve the level of understanding of the field for the doctoral students, familiarise them with the new developments and publications, and ensure that the resesarch of the professorship stays coordinated.
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• Lecture - Computational Foundations I
  By completing this module, students will have had a detailed exposition to two (mainly) imperative programming environments MATLAB and C/C++. They have learned the core language. Furthermore, students have understood a selection of data structures (arrays, trees, maps, hash tables, priority queues, sets), programming patterns, and core algorithms.
  Web Page | Moodle | TUMonline

• Lecture - Principles of Spatial Data Mining and Machine Learning
  By completing this module, students will be enabled to extract knowledge from spatial and spatio-temporal datasets following techniques from data mining and machine learning including linear models, kNN models, regression models, classification models, decision trees, NaiveBayes, Support Vector Machines and more. These methods are applied to spatial datasets including point clouds, trajectory datasets, event databases, spatial networks, text, and multimedia data. Students get an overview of methods and techniques to explore big geospatial datasets using data mining techniques.
  Web Page Moodle | TUMonline

• Lecture - Seminar Selected Topics in Big Geospatial Data
  In this module, students learn advanced techniques from big geospatial data management and analysis and are exposed to selected topics in a real-world context on the big geospatial data cluster and beyond.
  Web Page | Moodle | TUMonline