Machine Learning and Deep Learning Development

Course overview

Goals of the Training The focus of the Machine Learning and Deep Learning Development training is on understanding and applying machine learning and deep learning. The content includes basic and advanced techniques of machine learning as well as the development of models in the field of deep learning. Reinforcement learning is also covered to develop adaptive systems that learn from interactions. A seminar on current topics in Artificial Intelligence provides insights into the latest developments and trends in this dynamic field. Content of the Training The training content is in English. Machine Learning Supervised, unsupervised, and reinforcement learning approaches Regression and classification learning problems Estimation of functional dependencies via regression techniques Data clustering Support vector machines, large margin classification Decision tree learning Deep Learning Introduction to neural networks and deep learning Network architectures Neural network training Alternative training methods Further network architectures Reinforcement Learning Introduction to reinforcement learning Markov chains Bandit Q-Learning Reinforcement learning approaches Seminar: Current Topics in AI In this module, students will reflect on current developments in AI. To this end, pertinent topics will be introduced via articles that are then critically evaluated by the students in the form of a written essay.

Upcoming dates

• 2026-10-22T22:00:00.000Z · 2027-02-22T23:00:00.000Z · Duisburg · Blended Learning
• 2026-10-22T22:00:00.000Z · 2027-02-22T23:00:00.000Z · Nürnberg, Mittelfranken · Blended Learning
• 2026-10-22T22:00:00.000Z · 2027-02-22T23:00:00.000Z · Mainz am Rhein · Blended Learning
• 2026-10-22T22:00:00.000Z · 2027-02-22T23:00:00.000Z · Leipzig · Blended Learning
• 2026-10-22T22:00:00.000Z · 2027-02-22T23:00:00.000Z · Frankfurt am Main · Blended Learning