Artificial Intelligence: Reinforcement Learning in Python — 93% OFF Coupon

Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising Applications

★4.8 out of 5
49,866 students
English
Updated March 2026

Quick Facts — Course Summary

Here's a comprehensive overview of Artificial Intelligence: Reinforcement Learning in Python — including pricing, duration, instructor credentials, curriculum highlights, and coupon validity. All data is verified against Udemy listings on May 30, 2026.

Here's a quick overview of everything you need to know about Artificial Intelligence: Reinforcement Learning in Python before you enroll:

•Course Name: Artificial Intelligence: Reinforcement Learning in Python
•Platform: Udemy
•Coupon Last Verified: March 31, 2026
•Level: All Levels
•Topic: Development
•Subtopic: Python
•Total Time: 14h 30m of video content
•Language: English
•Access Type: Unlimited lifetime access + updates
•Certificate: Included upon completion from Udemy
•Main Skills: Apply gradient-based supervised machine learning methods to reinforcement learning · Understand reinforcement learning on a technical level · Understand the relationship between reinforcement learning and psychology
•Requirements: Calculus (derivatives) · Probability / Markov Models
•Current Price: $14.99 (was $199.99). You save $185.00 with 93% discount.
•How to Apply: Click the coupon button to activate your discount automatically
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Tip:For best results, apply the coupon in a regular browser window rather than incognito/private mode.

Skills You'll Master

By completing Artificial Intelligence: Reinforcement Learning in Python, you'll gain practical, job-ready skills in Development. The curriculum is designed by Lazy Programmer Team, Lazy Programmer Inc. to ensure you develop real-world competencies that employers value.

By the end of Artificial Intelligence: Reinforcement Learning in Python, you'll have these practical skills:

✓Apply gradient-based supervised machine learning methods to reinforcement learning .
✓Understand reinforcement learning on a technical level .
✓Understand the relationship between reinforcement learning and psychology .
✓Implement 17 different reinforcement learning algorithms .
✓Understand important foundations for OpenAI ChatGPT, GPT-4.

What You Need Before Starting

Before enrolling in Artificial Intelligence: Reinforcement Learning in Python, review the recommended prerequisites below. Meeting these requirements will help you follow the course material effectively and get the most out of your learning experience on Udemy.

Before enrolling in Artificial Intelligence: Reinforcement Learning in Python, make sure you have:

•Calculus (derivatives)
•Probability / Markov Models
•Numpy, Matplotlib
•Beneficial to have experience with at least a few supervised machine learning methods
•Gradient descent
•Good object-oriented programming skills

About This Udemy Course

The following is the full official course description for Artificial Intelligence: Reinforcement Learning in Python as published on Udemy by instructor Lazy Programmer Team, Lazy Programmer Inc.:

Ever wondered how AI technologies like OpenAI ChatGPT and GPT-4 really work? In this course, you will learn the foundations of these groundbreaking applications.

When people talk about artificial intelligence, they usually don’t mean supervised and unsupervised machine learning.

These tasks are pretty trivial compared to what we think of AIs doing - playing chess and Go, driving cars, and beating video games at a superhuman level.

Reinforcement learning has recently become popular for doing all of that and more.

Much like deep learning, a lot of the theory was discovered in the 70s and 80s but it hasn’t been until recently that we’ve been able to observe first hand the amazing results that are possible.

In 2016 we saw Google’s AlphaGo beat the world Champion in Go.

We saw AIs playing video games like Doom and Super Mario.

Self-driving cars have started driving on real roads with other drivers and even carrying passengers (Uber), all without human assistance.

If that sounds amazing, brace yourself for the future because the law of accelerating returns dictates that this progress is only going to continue to increase exponentially.

Learning about supervised and unsupervised machine learning is no small feat. To date I have over TWENTY FIVE (25!) courses just on those topics alone.

And yet reinforcement learning opens up a whole new world. As you’ll learn in this course, the reinforcement learning paradigm is very from both supervised and unsupervised learning.

It’s led to new and amazing insights both in behavioral psychology and neuroscience. As you’ll learn in this course, there are many analogous processes when it comes to teaching an agent and teaching an animal or even a human. It’s the closest thing we have so far to a true artificial general intelligence.  What’s covered in this course?
  • The multi-armed bandit problem and the explore-exploit dilemma
  • Ways to calculate means and moving averages and their relationship to stochastic gradient descent
  • Markov Decision Processes (MDPs)
  • Dynamic Programming
  • Monte Carlo
  • Temporal Difference (TD) Learning (Q-Learning and SARSA)
  • Approximation Methods (i.e. how to plug in a deep neural network or other differentiable model into your RL algorithm)
  • How to use OpenAI Gym, with zero code changes
  • Project: Apply Q-Learning to build a stock trading bot
If you’re ready to take on a brand new challenge, and learn about AI techniques that you’ve never seen before in traditional supervised machine learning, unsupervised machine learning, or even deep learning, then this course is for you.

See you in class!

"If you can't implement it, you don't understand it"
  • Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".
  • My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratch
  • Other courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?
  • After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times...
Suggested Prerequisites:
  • Calculus
  • Probability
  • Object-oriented programming
  • Python coding: if/else, loops, lists, dicts, sets
  • Numpy coding: matrix and vector operations
  • Linear regression
  • Gradient descent
WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:
  • Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)
UNIQUE FEATURES
  • Every line of code explained in detail - email me any time if you disagree
  • No wasted time "typing" on the keyboard like other courses - let's be honest, nobody can really write code worth learning about in just 20 minutes from scratch
  • Not afraid of university-level math - get important details about algorithms that other courses leave out

Compare Similar Courses

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Is the Artificial Intelligence: Reinforcement Learning in Python Coupon Worth It?

Expert review by Andrew Derek, Lead Course Analyst at CoursesWyn.•Last updated: March 31, 2026.

Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, Artificial Intelligence: Reinforcement Learning in Python is a high-value resource for learners seeking to build skills inDevelopment. Taught by Lazy Programmer Team, Lazy Programmer Inc. on Udemy, the 14h 30m course provides a structured progression from foundational concepts to advanced techniques— making it suitable for learners at all levels. The current coupon reduces the price by 93%, from $199.99 to $14.99, removing the primary financial barrier to enrollment.

✓What We Like (Pros)

  • Verified 93% price reduction makes this course accessible to learners on any budget.
  • Aggregate student rating of 4.8 out of 5 indicates high learner satisfaction.
  • Strong enrollment base with over 49,866 students demonstrates course popularity and trust.
  • Includes an official Udemy completion certificate and lifetime access to all future content updates.

!Keep in Mind (Cons)

The following limitations should be considered before enrolling in Artificial Intelligence: Reinforcement Learning in Python:

  • The depth of Development coverage may be challenging for absolute beginners without the listed prerequisites.
  • Lifetime access is contingent on the continued operation of the Udemy platform.
  • Hands-on projects and quizzes require additional time investment beyond video watch time.
Final Verdict: Worth It
This course offers exceptional value with current pricing
✓

Course Rating Summary

Artificial Intelligence: Reinforcement Learning in Python has earned an aggregate rating of 4.8 out of 5 from 49,866 verified student reviews on Udemy. Below is the detailed rating distribution showing learner satisfaction across all star levels.

4.8
★★★★★
49,866 Verified Ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

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

Instructor Profile

Lazy Programmer Team, Lazy Programmer Inc. is the instructor behind Artificial Intelligence: Reinforcement Learning in Python on Udemy. Learn about their teaching background, subject matter expertise, and instructional approach to determine if this course matches your learning style.

Artificial Intelligence: Reinforcement Learning in Python is taught by Lazy Programmer Team, Lazy Programmer Inc., 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.

•Subject Area: Development
•Teaching Approach: Practical, project-based instruction focused on real-world application of Development skills.

Frequently Asked Questions

The following questions and answers cover the most common queries about Artificial Intelligence: Reinforcement Learning in Python, its coupon code, pricing, and enrollment process.

About the Author

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Andrew Derek

Lead Course Analyst at CoursesWyn with 8+ years of experience evaluating online learning platforms. I've analyzed 500+ Udemy courses and helped thousands of learners choose the right courses for their career goals.

⭐4.8/5 Rating
✓Trusted by 10K+ Students

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