Will I get a certificate after completing this course?

Yes. Upon successful completion, Udemy issues a certificate of completion that you can share on LinkedIn or add to your resume.

Advanced AI: Deep Reinforcement Learning in PyTorch (v2) — 90% Off Coupon

Q: Is the coupon for "Advanced AI: Deep Reinforcement Learning in PyTorch (v2)" still valid?

The coupon listed on this page was verified on November 4, 2025. It applies a 90% discount and is valid until November 30, 2025. Coupons can expire quickly — click "Redeem Coupon" to check current availability.

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

The course is approximately 15h 30m of on-demand video content. You get lifetime access, so you can study at your own pace.

Q: What will I learn in "Advanced AI: Deep Reinforcement Learning in PyTorch (v2)"?

This course covers: 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. See the full curriculum on the Udemy course page for a complete breakdown.

Q: Do I need any prior knowledge to take this course?

The instructor recommends: 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.).

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

⭐ 4.7 out of 5(1,942 students enrolled)Created by Lazy Programmer Inc., and Lazy Programmer TeamLast updated: November 2025🌐 English

Course Overview - Key Takeaways

The following summarizes all verified data points for this course, including pricing, duration, instructor, and coupon validity. All data is sourced directly from Udemy and verified by CourseSpeak on November 4, 2025.

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

•Provider: Udemy (listed via CourseSpeak)

•Instructor: Lazy Programmer Inc., Lazy Programmer Team

•Coupon Verified On: November 4, 2025

•Difficulty Level: Advanced

•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: 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 · Undergraduate STEM math: calculus, probability, statistics

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

•Coupon: Click REDEEM COUPON below to apply discount

⚠️

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What You'll Learn

This course 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.

Course Requirements & Prerequisites

The following background knowledge and tools are recommended before starting this course. 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 as published on Udemy by instructors Lazy Programmer Inc., Lazy Programmer Team. It covers the curriculum structure, teaching methodology, and topic scope for this Development course:

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Is the Advanced AI: Deep Reinforcement Learning in PyTorch (v2) Coupon Worth It?

Expert review by Josh Smith, Lead Course Reviewer at CourseSpeakUpdated Nov 4, 2025

The short answer is yes — provided the Development skills this course teaches actually line up with what you want to build. The regular price for Advanced AI: Deep Reinforcement Learning in PyTorch (v2) on Udemy is $109.99. The coupon code listed on this page drops that 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 — less than the cost of a single chapter of most printed development textbooks.

A discount is only worth something if the material delivers, and the curriculum here is built around practical 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) — concrete skills you can apply, not abstract theory. It has already been taken by 1,942 students and holds a 4.7-star average from verified reviews, which is a reasonable sign the content holds up in practice.

The prerequisites are worth reading before you commit: Reinforcement Learning fundamentals: MDPs, Bellman Equation, Monte Carlo Methods, Temporal Difference Learning; Undergraduate STEM math: calculus, probability, statistics. This one suits learners who already have some grounding in Development. In practical terms, expect around 15h 30m of on-demand video to work through at your own pace. The material is presented in English.

Pros

✓Verified 90% price reduction.
✓High learner satisfaction (4.7/5).
✓Trusted by 1,942 students.
✓Certificate + lifetime access.

Cons

!The coupon is time-limited — once it expires, the price tends to revert toward the standard $109.99.
!Lifetime access is tied to Udemy staying online; the platform can change its policies.
!Budget for the exercises and quizzes too — they add real time on top of the 15h 30m of video.
!Assumes some prior knowledge — check the prerequisites before purchasing.

Josh Smith

Lead Course Reviewer

Credentials →

"At roughly $0.71 an hour of video, Advanced AI: Deep Reinforcement Learning in PyTorch (v2) is priced sensibly for what it actually covers — review Reinforcement Learning Basics: MDPs, Bellman Equation, Q-Learning and beyond. If Development is on your roadmap and you value the 4.7-star track record, this coupon is worth using while it's still valid."

✓

Final Verdict: Worth It

Saves you $99.00 against the standard Udemy price

New to redeeming coupons? Visit our step-by-step guide for detailed instructions on how to apply coupon codes.Coupon last verified November 4, 2025.At $10.99 you save $99.00 compared to the standard $109.99 price, and Udemy coupons are time-limited — redeem as soon as possible.

Course Rating Summary

This course 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

75%

4 stars

15%

3 stars

2 stars

1 star

* Rating distribution is approximated from the aggregate score. Sourced from Udemy. Last verified: November 4, 2025.

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Instructor Profiles

Background information on Lazy Programmer Inc., Lazy Programmer Team, the instructors responsible for this course on Udemy.

Lazy Programmer Inc.

Udemy Instructor

Full Profile ↗

Subject Area

Development

Total Students

1,942+ enrolled

Rating

4.7 / 5.0

Course Duration

15h 30m

Teaching Approach

Practical, project-based instruction built around real-world application of Development skills, with hands-on exercises and quizzes to reinforce each section.

Lazy Programmer Team