Reinforcement & Machine Learning with Python

Course overview

Upon completion of the training, you will have knowledge in the design and implementation of reinforcement and machine learning algorithms using Python. You will also be able to model neural networks and decision processes in Markov decision processes. Basic Machine Learning Data preparation for machine learning with Python Clustering methods (e.g., k-Means) with Scikit-Learn Model evaluation and hyperparameter tuning Reinforcement Learning Markov decision processes (MDP) Q-Learning and SARSA Deep reinforcement learning with Python Policy gradient methods

Upcoming dates

• 2026-08-02T22:00:00.000Z · 2026-11-29T23:00:00.000Z · München · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-11-29T23:00:00.000Z · Bremen · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-11-29T23:00:00.000Z · Hamburg · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-11-29T23:00:00.000Z · Mönchengladbach · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-11-29T23:00:00.000Z · Düsseldorf · Combined Learning