2100015 – Maschinelles Lernen für Robotiksysteme 2

Machine Learning for Robotic Systems 2 is a lecture with hands-on exercises that delves into advanced machine learning techniques tailored for robotic applications. The lecture covers a wide range of topics—including Active Learning, Transformers, Adversarial Learning, GANs, Deep Reinforcement Learning, Goal-Directed Exploration, Recurrent Neural Networks, and Imitation Learning—ensuring you build a robust foundation in modern robotics AI. Through a mix of theoretical insights and practical programming sessions, you'll learn to implement these cutting-edge methods. No prior experience from the lecture Machine Learning for Robotic Systems 1 is required, making this course accessible to anyone eager to explore the field.