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.