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★ 4.8 rated · $9.99
Build Artificial Intelligence (AI) agents using Reinforcement Learning in PyTorch: DQN, A2C, Policy Gradients, +More!
$10.99 with coupon (list $109.99 — save $99.00, 90% off)
Coupon Verified: November 4, 2025 · click Claim Coupon to apply the discount code
Our verdict: worth it — as long as the Development skills on the syllabus match what you actually want to learn. The regular price for Advanced AI: Deep Reinforcement Learning in PyTorch (v2) on Udemy is $109.99. With the coupon code on this page, that falls to $10.99 — a saving of $99.00, or 90% off the standard rate Spread across 15h 30m of on-demand video, that works out to roughly $0.71 per hour of content — cheaper than a single chapter of most printed Development textbooks.
A cheap price means nothing if the material is thin — here the syllabus is organized around usable outcomes. Lazy Programmer Inc. and Lazy Programmer Team walk you through review Reinforcement Learning Basics: MDPs, Bellman Equation, Q-Learning, theory and Implementation of Deep Q-Learning / DQN, and theory and Implementation of Policy Gradient Methods and A2C (Advantage Actor-Critic) — skills meant to be used, not just watched. It has already been taken by 1,942 students and holds a 4.7-star average from verified reviews, which suggests the content holds up once learners actually apply it.
Check the prerequisites before you commit: Reinforcement Learning fundamentals: MDPs, Bellman Equation, Monte Carlo Methods, Temporal Difference Learning; Undergraduate STEM math: calculus, probability, statistics. Best suited to learners who already have footing in Development. Plan for roughly 15h 30m of on-demand video at your own pace. Lessons are delivered in English.
Practical skills and outcomes you'll gain from Advanced AI: Deep Reinforcement Learning in PyTorch (v2) — taken from the official Udemy syllabus for Development learners.
Review Reinforcement Learning Basics: MDPs, Bellman Equation, Q-Learning.
Theory and Implementation of Deep Q-Learning / DQN.
Theory and Implementation of Policy Gradient Methods and A2C (Advantage Actor-Critic).
Apply DQN and A2C to Atari Environments (Breakout, Pong, Asteroids, etc.).
VIP Only: Apply A2C to Build a Trading Algorithm for Multi-Period Portfolio Optimization.
What you need before enrolling in Advanced AI: Deep Reinforcement Learning in PyTorch (v2) — prerequisites as listed by the instructor on Udemy.
Reinforcement Learning fundamentals: MDPs, Bellman Equation, Monte Carlo Methods, Temporal Difference Learning
Undergraduate STEM math: calculus, probability, statistics
Python programming and numerical computing (Numpy, Matplotlib, etc.)
Deep Learning fundamentals: Convolutional neural networks, hyperparameter optimization, etc.
The full official description of Advanced AI: Deep Reinforcement Learning in PyTorch (v2) — curriculum, teaching approach, and everything included with this Udemy coupon.
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Common queries about this coupon, pricing, and enrollment. Answers reflect our last check on November 4, 2025.
★ 4.8 rated · $9.99
★ 4.8 rated · $9.99
★ 4.9 rated · $9.99
★ 4.8 rated · $9.99
★ 4.8 rated · $9.99
★ 4.8 rated · $9.99
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