In this immersive workshop, participants will delve into fundamental concepts of reinforcement learning, including Multi-Armed Bandits, Markov Decision Processes, and Tabular Methods. Moving beyond basics, advanced techniques like Deep Q-Learning, Policy Gradient, and Actor-Critic Methods will be explored. Hands-on Python practice sessions will empower participants to apply theoretical knowledge, ensuring a comprehensive understanding of intelligent decision-making systems.