Reinforcement Learning I

Most AI systems learn from existing data. But what if no data exists? And what if even humans don’t yet know how to solve the problem in question?

In this beginner-friendly workshop, you will explore how Reinforcement Learning (RL) enables machines to learn from experience through trial and error, guided only by rewards. Hands-on coding exercises will demonstrate how interaction replaces supervision and how feedback drives "intelligent" behaviour — much like learning in animals and humans.

You will learn how agents interact with their environment, make decisions, and improve over time. The workshop uses interactive and practical formats to build an intuitive understanding of key RL concepts such as agent–environment interaction, the exploration–exploitation trade-off and the role of reward design.

The workshop provides orientation in a field that plays a central role in domains such as robotics, logistics, control tasks and game development.

Requirements

Basic knowledge of Python is recommended. No prior experience with Reinforcement Learning is required. This is an introductory workshop and not suited for participants with existing RL knowledge.

Please bring a laptop with you and install the necessary developer tools in advance. You will receive the relevant information after registering.

Registration & participation

Registration is binding. If you are unable to attend, please cancel your ticket in good time to allow other participants to take your place.

Important Information

Photographs, audio recordings and films will be made during the event. By participating in the event, you agree that photos, audio and video recordings in which you are recognizable may be published as part of the public relations work of the AI Service Center Berlin-Brandenburg and the HPI.

The is a project of the Federal Ministry of Research, Technology and Space. Its aim is to lower the barriers for using AI in business and society.

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