Autonom­ous Learn­ing

Recommended prerequisites
 

Pattern Recognition and Machine Learning I, Experimentation and Evaluation in Machine Learning
(or knowledge from courses with similar content).
 
Syllabus

  • Basic concepts of autonomous learning in technical systems
  • Approaches for hyperparameter optimisation
  • Basic introductions to:
    • active learning
    • collaborative learning
    • transfer learning
    • Reinforcement Learning
  • Self-Awareness and self-reflection in technical systemen
  • Meta-Learning
  • Applications  

Targeted Proficiency  

The students will be able to successfully:

  • Explain various concepts from the field of autonomous learning in technical systems.
  • Design and develop intelligent technical systems with autonomous learning abilities.
  • Evaluate and compare different autonomous learning approaches.