• What is RL and how is it different from other AI topics?
• The RL vocabulary: states, actions, rewards and policies
• Value functions and the Bellman equations
• Solving an RL problem: Dynamic Programming and Q-learning
• Scaling up RL: function approximations in deep RL

Participants will have an intermediate understanding of RL concepts and methodologies that will enable them to access recent literature and apply RL methodologies to similar problems.

• Python programming
• Google account (for using Colab)
• Own laptop with a modern browser
• For more information and access to the notebooks, go to: https://gitlab.com/tothepoint/reinforcement-learning-workshop/notebooks