Paulescu/hands-on-rl resource

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1572 stars · 194 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A free, hands-on Reinforcement Learning course taught through Jupyter Notebooks, taking learners from basic RL concepts to deep RL. It covers Q-learning, SARSA, parametric and deep Q-learning, and policy gradients through progressively harder problems like Taxi, Mountain Car, Cart Pole, and Lunar Lander.

Use cases

• learn reinforcement learning from scratch
• understand q-learning with a worked example
• study sarsa on the mountain car problem
• learn deep q networks with cart pole
• understand policy gradients with lunar lander
• find a free hands-on RL course with python notebooks

When to choose

• you are a beginner wanting a step-by-step practical RL course
• you prefer learning by coding in Jupyter notebooks
• you want intuition and tips explained alongside theory
• you do not yet know deep learning but want to reach deep RL

When to avoid

• you need a production RL library or framework
• you want a formal university-style theoretical treatment
• you need coverage of the latest RL algorithms like PPO or RLHF
• you need actively updated content for recent library versions

Facets

learning-resource · maturity maintenance

reinforcement-learning machine-learning deep-learning reinforcement-learning machine-learning tutorials education python cross-platform free-course jupyter-notebooks q-learning sarsa policy-gradients deep-q-learning gym-environments

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