Cutting-Edge AI: Deep Reinforcement Learning in PyTorch (v2)

About this course

This course contains the use of artificial intelligence (it's an AI course, duh!).

The world of Artificial Intelligence is moving fast, and Deep Reinforcement Learning (DRL) is the engine driving its most impressive breakthroughs—from mastering complex games to autonomous robotics and high-frequency trading.

Welcome to Version 2. We’ve completely rebuilt this course from the ground up to reflect the modern AI landscape. This isn't just a minor update; it’s a total transformation designed to take you from a curious coder to a DRL expert.

Why Version 2?

We listened to your feedback and updated every component to ensure you’re learning with the most relevant, industry-standard tools available today:

PyTorch Native: We’ve ditched the clunky syntax of TensorFlow 1 for the elegance and flexibility of PyTorch, the preferred framework for AI researchers worldwide.

Free MuJoCo Integration: Take advantage of the industry-leading physics engine, MuJoCo, which is now open-source and free to use for your robotics simulations.

Refined Explanations: We’ve streamlined the theory, making the "math-heavy" concepts intuitive, clear, and actually fun to learn.

What You’ll Master

This course bridges the gap between academic theory and production-ready code. You won't just learn how to use libraries; you’ll learn how to build these sophisticated agents from scratch.1. The Foundations (The RL Brain)Before diving into deep networks, we ensure your foundation is rock-solid. You’ll master Markov Decision Processes (MDPs) and the Bellman Equation - the mathematical heart of how an agent "values" its future.2. Deep Deterministic Policy Gradient (DDPG)Learn the algorithm tha

Prices, discounts and availability are set by Udemy. We may earn a commission when you purchase through links on this site.