Get Advanced AI: Deep Reinforcement Learning in PyTorch (v2) with 90% OFF Udemy Coupon

Build Artificial Intelligence (AI) agents using Reinforcement Learning in PyTorch: DQN, A2C, Policy Gradients, +More!.

4.7 out of 5
(1,942 students enrolled)
Instructor: Lazy Programmer Inc., Lazy Programmer Team
Last Update:
Language: English

Key Takeaways — Course Overview

The following summarizes all verified data points for Advanced AI: Deep Reinforcement Learning in PyTorch (v2), including pricing, duration, instructor, and coupon validity. All data is sourced directly from Udemy and verified by CoursesWyn on .

Course Title: Advanced AI: Deep Reinforcement Learning in PyTorch (v2)

Platform: Udemy (listed via CoursesWyn)

Instructor: Lazy Programmer Inc., Lazy Programmer Team

Coupon Verified:

Difficulty Level: All Levels

Category: Development

Subcategory: Reinforcement Learning

Duration: 15h 30m of on-demand video

Language: English

Access: Lifetime access to all course lectures and updates

Certificate: Official certificate of completion issued by Udemy upon finishing all course requirements

Top Learning Outcomes: Students who complete Advanced AI: Deep Reinforcement Learning in PyTorch (v2) will be able to: 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)

Prerequisites: Reinforcement Learning fundamentals: MDPs, Bellman Equation, Monte Carlo Methods, Temporal Difference Learning

Price: $10.99 with coupon / Regular Udemy price: $109.99. Applying this coupon saves you $99.00 (90% OFF).

Important:

This coupon may not function properly in private/incognito browsing mode. Use a standard browser window and temporarily disable ad blockers or VPN services before clicking the redemption link to ensure the discount is applied correctly.

What You'll Learn

Completing Advanced AI: Deep Reinforcement Learning in PyTorch (v2) gives you the following verified skills and competencies in Development:

  • 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

Requirements

The following background knowledge and tools are recommended before starting Advanced AI: Deep Reinforcement Learning in PyTorch (v2). Students without these prerequisites may still enroll but should expect a steeper learning curve.

  • 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.

About This Udemy Course

The following is the full official course description for Advanced AI: Deep Reinforcement Learning in PyTorch (v2) as published on Udemy by instructor Lazy Programmer Inc., Lazy Programmer Team. It covers the curriculum structure, teaching methodology, and topic scope for this Development course.

Are you ready to unlock the power of Reinforcement Learning (RL) and build intelligent agents that can learn and adapt on their own? Welcome to the most comprehensive, up-to-date, and practical course on **Reinforcement Learning**, now in its highly improved Version 2! Whether you're a student, researcher, engineer, or AI enthusiast, this course will guide you from foundational RL concepts to advanced Deep RL implementations — including building agents that can play Atari games using cutting-edge algorithms like DQN and A2C. What You’ll Learn - Core RL Concepts: Understand rewards, value functions, the Bellman equation, and Markov Decision Processes (MDPs). - Classical Algorithms: Master Q-Learning, TD Learning, and Monte Carlo methods. - Hands-On Coding: Implement RL algorithms from scratch using Python and Gymnasium. - Deep Q-Networks (DQN): Learn how to build scalable, powerful agents using neural networks, experience replay, and target networks. - Policy Gradient & A2C: Dive into advanced policy optimization techniques and learn how actor-critic methods work in practice. - Atari Game AI: Use modern libraries like Stable Baselines 3 to train agents that play classic Atari games — from scratch! - Bonus Concepts: Explore evolutionary methods, entropy regularization, and performance tuning tips for real-world applications. Tools and Libraries - Python (with full code walkthroughs) - Gymnasium (formerly OpenAI Gym) - Stable Baselines 3 - NumPy, Matplotlib, PyTorch (where applicable) Why This Course? - Version 2 updates: Streamlined content, clearer explanations, and updated libraries. - Real implementations: Go beyond theory by building working agents — no black boxes. - For all levels: Includes a dedicated review section for beginners and deep dives for advanced learners. - Proven structure: Designed by an experienced instructor who has taught thousands of students to success in AI and machine learning. Who Should Take This Course? - Data Scientists and ML Engineers who want to break into Reinforcement Learning - Students and Researchers looking to apply RL in academic or practical projects - Developers who want to build intelligent agents or AI-powered games - Anyone fascinated by how machines can learn through interaction Join thousands of learners and start mastering Reinforcement Learning today — from theory to full implementations of agents that think, learn, and play. Enroll now and take your AI skills to the next level!

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Is This Course Worth It?

Expert review by Andrew Derek, Lead Course Reviewer at CoursesWyn. Last updated: .

Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, Advanced AI: Deep Reinforcement Learning in PyTorch (v2) is a high-value resource for learners seeking to build skills in Development. Taught by Lazy Programmer Inc., Lazy Programmer Team on Udemy, the 15h 30m course provides a structured progression from foundational concepts to advanced Reinforcement Learning techniques — making it suitable for learners at all levels. The current coupon reduces the price by 90%, from $109.99 to $10.99, removing the primary financial barrier to enrollment.

What We Like (Pros)

The following advantages were identified:

  • Verified 90% price reduction makes this course accessible on any budget.
  • Aggregate student rating of 4.7 out of 5 indicates high satisfaction.
  • Includes an official Udemy completion certificate and lifetime access.

Keep in Mind (Cons)

The following limitations should be considered:

  • The depth of Reinforcement Learning coverage may be challenging for newcomers.
  • Lifetime access is contingent on the Udemy platform's operation.
  • Hands-on projects require additional time beyond video watch time.

Andrew Derek

Lead Reviewer

View credentials →

"Given the 90% price reduction and verified 4.7-star rating, Advanced AI: Deep Reinforcement Learning in PyTorch (v2) represents one of the strongest value propositions currently available in Development. Enrollment is recommended while this coupon remains active."

Final Verdict: Worth It

Course Rating Summary

Advanced AI: Deep Reinforcement Learning in PyTorch (v2) holds an aggregate rating of 4.7 out of 5 based on 1,942 student reviews on Udemy. The distribution below shows the approximate percentage of students who gave each star rating.

4.7

1,942 Verified Ratings

5 stars
94%
4 stars
13%
3 stars
4%
2 stars
1%
1 star
1%

* Rating distribution is approximated from the aggregate score. Sourced from Udemy. Last verified: .

Instructor Profile

The following section provides background information on Lazy Programmer Inc., Lazy Programmer Team, the instructor responsible for creating and maintaining Advanced AI: Deep Reinforcement Learning in PyTorch (v2) on Udemy.

Advanced AI: Deep Reinforcement Learning in PyTorch (v2) is taught by Lazy Programmer Inc., Lazy Programmer Team, a Udemy instructor specializing in Development. For the full instructor biography, professional credentials, and a complete list of their courses, visit the official instructor profile on Udemy.

  • Instructor Name: Lazy Programmer Inc., Lazy Programmer Team

  • Subject Area: Development

  • Teaching Approach: Practical, project-based instruction focused on real-world application of Reinforcement Learning skills.

Coupon Help Center

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Frequently Asked Questions

The following questions and answers cover the most common queries about Advanced AI: Deep Reinforcement Learning in PyTorch (v2), its coupon code, pricing, and enrollment process. All answers are based on verified data from Udemy as of .

Is there a verified discount coupon for Advanced AI: Deep Reinforcement Learning in PyTorch (v2)?

Yes. A verified Udemy coupon for Advanced AI: Deep Reinforcement Learning in PyTorch (v2) is available on this page, reducing the price from $109.99 to $10.99 — a saving of $99.00 (90% OFF). The coupon was last verified on March 26, 2026.

How do I apply the Advanced AI: Deep Reinforcement Learning in PyTorch (v2) coupon code?

Click the "Redeem Coupon" button on this page. The 90% discount is automatically applied to the Udemy checkout link. No manual coupon entry is needed.

How long is the Advanced AI: Deep Reinforcement Learning in PyTorch (v2) course on Udemy?

Advanced AI: Deep Reinforcement Learning in PyTorch (v2) consists of 15h 30m of on-demand video. Udemy provides lifetime access to enrolled students, allowing you to revisit all content at any time after purchase.

What skills will I gain from Advanced AI: Deep Reinforcement Learning in PyTorch (v2)?

Advanced AI: Deep Reinforcement Learning in PyTorch (v2), taught by Lazy Programmer Inc., Lazy Programmer Team on Udemy, covers the following competencies: 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). These skills are delivered through 15h 30m of structured Reinforcement Learning content, enabling learners to apply knowledge immediately after each module.

What is the Advanced AI: Deep Reinforcement Learning in PyTorch (v2) Udemy course?

Advanced AI: Deep Reinforcement Learning in PyTorch (v2) is a 15h 30m online course on Udemy, created and taught by Lazy Programmer Inc., Lazy Programmer Team. It covers Development topics and holds a 4.7-star rating from 1,942 enrolled students. Use the verified coupon on this page to access it at $10.99 (90% OFF the regular $109.99 price).
Andrew Derek

Andrew Derek

Expert Reviewer

Andrew Derek is a lead editor and course analyst at CoursesWyn with over 8 years of experience in online education and digital marketing. He meticulously audits every Udemy coupon and course syllabus to ensure students get the highest quality learning materials at the best possible price.

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