L-11 Learning Agents using Q-Learning (Theory and code) | Agentic AI Course

In this video, we break down Q-Learning, one of the most important algorithms in Reinforcement Learning (RL). Whether you’re a beginner in machine learning or revisiting the topic, this lecture will guide you through both theory and coding Q-Learning from scratch using Python.

We’ll cover:
✅ What is a Learning Agent?
✅ Fundamentals of Q-Learning and how it works
✅ The Epsilon-Greedy strategy
✅ How to initialize and update a Q-Table
✅ Step-by-step Python implementation of Q-Learning in a simple environment

GitHub: https://github.com/AarohiSingla/Agent...

For collaborations, sponsorships, or other inquiries, feel free to contact me at: [email protected]

🔍 What You’ll Learn:

1- What is a Learning Agent?
2- Basics of Q-Learning and how it works
3- Epsilon-Greedy strategy explained
4- Q-Table initialization and updates
5- Coding Q-Learning from scratch with a simple environment