Complete Reinforcement Learning Tutorial Series with Python

Description

Course Curriculum

Module 1: Fundamentals of Bellman Equations in Reinforcement Learning

  • Fundamentals of Bellman Equations in Reinforcement Learning
    00:00

Module 2: Advanced Concepts of Bellman Equations for Reinforcement Learning

Module 3: Dynamic Programming Methods in Reinforcement Learning

Module 4: Monte Carlo Methods for Reinforcement Learning

Module 5: Q-Learning for Ride-Sharing Systems (OpenAI Taxi Environment)

Module 6: Deep Q-Networks Applied to Pong Game

Module 7: Policy Gradient Techniques in Reinforcement Learning

Module 8: Actor-Critic (A3C) Algorithm Tutorial

Module 9: Actor-Critic Methods for Continuous Action Spaces

Module 10: Proximal Policy Optimization (PPO) for Robotics Training in Roboschool

Module 11: Augmented Random Search for Robot Locomotion Training

Module 12: AlphaGo Zero Introduction and System Overview

Module 13: AlphaGo Zero – Monte Carlo Tree Search Explained

Module 14: AlphaGo Zero – Neural Network Architecture Design

$14.00 $114.00
  • Level
    Intermediate
  • Last Updated
    June 4, 2026