Reinforcement Learning Foundations: A Practical Audio Guide to Core Concepts, Intuition, and Implementation Basics

Adam Novak

Master reinforcement learning and build intelligent AI algorithms without getting lost in dense mathematical equations. Perfect for your daily commute, this intellectually stimulating audio experience transforms complex data science concepts into...

Premium Chapters

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Opening Credits

1/13/2026

Chapter 1: Learning by Doing The Core Idea of Reinforcement Learning

1/13/2026

Chapter 2: From Stories to Systems Markov Decision Processes and Return

1/13/2026

Chapter 3: Value, Policy, and the Art of Balancing Curiosity and Caution

1/13/2026

Chapter 4: Learning from Episodes Monte Carlo Reinforcement Learning

1/13/2026

Chapter 5: Learning from Fragments Temporal Difference Intuition

1/13/2026

Chapter 6: From Prediction to Control Tabular Q Learning and SARSA

1/13/2026

Chapter 7: Beyond Tables Function Approximation and Deep Value Learning

1/13/2026

Chapter 8: Shaping Behavior Reward Design, Discounting, and Sparse Feedback

1/13/2026

Chapter 9: Directly Learning to Act Policy Gradients and Beyond

1/13/2026

Chapter 10: Planning, Learning, and Practice Model Based Methods and Real World Workflows

1/13/2026

Closing Credits

1/13/2026