Teaching Winter Term 2022 / 2023

Welcome to the teaching page for winter term 2022 / 2023. Here you find all resources and information.

• Lecture - Computational Foundations I
  By completing this module, students will have had a detailed exposition to computing. They have learned the core of the modern programming language C++. 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/Videos | TUMonline

• Lecture - Principles of Programming
  In this course, students are introduced to advanced programming and algorithms with examples in Python and C++. It shall as well include some examples from computational geometry, point cloud processing, image analysis, etc. to - at the same time - introduce canonical patterns or even core libraries for working with data from subfields of geodesy.
  Web Page | Moodle/Videos | TUMonline

• 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 - 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, Support Vector Machines and more. These methods are applied to spatial datasets including satellite images, spatial networks, and geo-social media data. Students get an overview of methods and techniques to explore big geospatial datasets using data mining techniques.
  Web Page | Moodle/Videos | 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. In this semester, we are going to concentrate on embedded AI with a project on dead wood reckognition.
  Web Page | Moodle/Videos | TUMonline