This repository provides a structured educational course on reinforcement learning, progressing from foundational concepts like Q-learning and SARSA to deep RL techniques. Each chapter solves progressively difficult problems in Jupyter notebooks, covering classic RL environments including Taxi, Mountain Car, Cart Pole, and Lunar Lander. The course requires no prior deep learning knowledge and provides context on how DL integrates with modern reinforcement learning.