IE 678: Deep Learning (FSS 2024)


  • Lecturer:Prof. Dr. Rainer Gemulla, Simon Forbat
  • Type of course: Lecture (in presence), exercises, assignments (6 ECTS points)
  • Prerequisites: IE 675b Machine Learning or equivalent
  • Registration: enroll in ILIAS

Lecture (Thursday) starts in the first week, tutorial (Tuesday) in the second week. Lecture notes, exercises, assignments, and supplementary material can be found in ILIAS.


Machine learning is concerned with building computer systems that improve with experience as well as the study of learning processes, including the design of algorithms that are able to make predictions or extract knowledge from data. Building upon IE 675b Machine Learning, this course focuses on deep learning and introduces basic and advanced deep learning architectures and techniques, training methods and hyperparameter optimization, as well as selected applications.

Tentative topics include:

  • Feedforward neural networks
  • Backpropagation and parameter optimization
  • Machine learning systems
  • Training techniques for deep learning models
  • Recurrent neural networks
  • Convolutional neural networks
  • Attention and Transformers
  • Deep learning for graphs
  • Deep generative modelling