Reinforcement Learning with Python

Learn reinforcement learning fundamentals and advanced applications through hands-on Python programming in this comprehensive 6-hour tutorial series. Master deep reinforcement learning concepts by building AI agents that play classic Atari games like Space Invaders, create custom training environments using OpenAI Gym, and develop trading algorithms for financial markets including GameStop stock analysis. Explore practical implementations covering beginner-friendly introductions to RL concepts, deep Q-learning networks for game playing, custom environment design, algorithmic trading strategies, and custom indicator development for financial applications. Gain experience with popular Python libraries and frameworks while building real-world projects that demonstrate the power of reinforcement learning across gaming and financial domains.

Syllabus

Deep Reinforcement Learning Tutorial for Python in 20 Minutes
Deep Reinforcement Learning for Atari Games Python Tutorial | AI Plays Space Invaders
Building a Custom Environment for Deep Reinforcement Learning with OpenAI Gym and Python
A.I. Learns to Play Space Invaders | Reinforcement Learning
Python Reinforcement Learning Tutorial for Beginners in 25 Minutes
Reinforcement Learning for Trading Tutorial | $GME RL Python Trading
Custom Indicators for Reinforcement Learning Trading Tutorial | $GME Python Trading PT2
Reinforcement Learning in 3 Hours | Full Course using Python