Zum Inhalt springen Zur Suche springen

Planning Elective Modules

In order to plan your courses beyond obligatory courses, you may take a look at the module handbook as well as the list of courses from the past and our tentative plans for the future. Keep in mind that the plans for the future are not set in stone yet. In particular, there will be additional courses that happen irregularly.

In the LSF you can look up the past 4 semesters. Here are direct links to the elective courses in the AI master programme:

Tentative preview of what's upcoming:

Winter 24/25

  • Introduction to Logic Programming
  • Introduction to Linear Programming
  • Natural Language Processing
  • Methods for Population Genetics
  • Growth Mechanics
  • Advanced Topics in Bayesian Data Science
  • Data & Knowlege Engineering (DKE)
  • Deep Learning in Life Science: Generative Models
  • Neuroimaging and Precision Medicine
  • Reinforcement Learning
  • Topological Data Analysis
  • Algorithmic Advances in Computational Genomics
  • Master's Seminar: Computational Argumentation
  • Master's Seminar: Digital Innovation and Entrepreneurship
  • Master's Seminar: Ethics in Natural Language Processing

Summer 25

  • Algorithms for Sequence Analysis
  • Computer Vision
  • Create Your Tech Startup
  • Growth Mechanics
  • Introduction to Statistical Analysis through Computer Simulations
  • Stochastic Models of Biological Systems
  • Approximation algorithms for clustering problems
  • Dialogue Systems
  • Information Theory
  • Philosophy of Intelligence
  • Master's Seminar on Combinatorial Optimization in Bioinformatics
  • Master's Seminar on Privacy-preserving Machine Learning
  • Master's Seminar: Property Testing
  • Master's Seminar: Word Embedding Spaces
  • Master’s Seminar Advances in Data Science

Winter 25/26

  • Introduction to Logic Programming
  • Introduction to Linear Programming
  • Natural Language Processing
  • Methods for Population Genetics
  • Neuroimaging and Precision Medicine
  • Master's Seminar: Computational Argumentation
  • Master's Seminar: Digital Innovation and Entrepreneurship

Summer 26

  • Algorithms for Sequence Analysis
  • Computer Vision
  • Create Your Tech Startup
  • Growth Mechanics
  • Introduction to Statistical Analysis through Computer Simulations
  • Stochastic Models of Biological Systems
  • Deep Learning: Representation Learning
  • Markov Chains
  • Spectral Graph Theory and Graph Signal Processing
  • Master’s Seminar Advances in Data Science