10 Best Deep Reinforcement Learning Courses You Must Know in 2025

Are you looking for Best Deep Reinforcement Learning Courses?… If yes, this article is for you. In this article, you will find the 10 Best Deep Reinforcement Learning Courses. So give your few minutes and find out the Best Deep Reinforcement Learning Courses for you.

Now without any further ado, let’s get started-

Best Deep Reinforcement Learning Courses

1. Become a Deep Reinforcement Learning Expert– Udacity

Rating-	4.6/5
Time to Complete-	4 months (If you spend 10 hours per week)
Paid/FREE-	Paid
Programming Language Used-	Python

This Become a Deep Reinforcement Learning Expert is an advanced Nanodegree Program offered by Udacity. This program is not for beginners. In this Nanodegree program, you will learn reinforcement learning fundamentals.

This Nanodegree program is based on practical learning which means you will work on various projects to strengthen your concepts of reinforcement learning.

By applying deep learning architectures to reinforcement learning tasks, you will understand the concepts. This Nanodegree program will also cover the theory of evolutionary algorithms and policy-gradient methods. 

Their Technical mentor support will help you and guide you throughout the Nanodegree Program.

There are 4 courses in this program.

Courses Include-

1. Foundations of Reinforcement Learning
2. Value-Based Methods
3. Policy-Based Methods
4. Multi-Agent Reinforcement Learning

Extra Benefits-

• You will get a chance to work on Real-world projects.
• You will get Technical mentor support.
• Along with that, you will get Resume services, Github review, and LinkedIn profile review.

Drawbacks-

• This Nanodegree Program is expensive.

Best For-

• Those who have Intermediate to advanced Python experience and intermediate statistics and machine learning knowledge.

Interested to Enroll?

If yes, then check it out here– Become a Deep Reinforcement Learning Expert

2. Reinforcement Learning– Udacity

Rating-	NA
Time to Complete-	4 months
Paid/FREE-	FREE
Programming Language Used-	Java

This Reinforcement Learning is an advanced-level FREE deep learning course on Udacity. This course is also not for beginners. For this course, you should have intermediate-level machine learning knowledge.

The previous Nanodegree program covered reinforcement learning from a practical perspective but this course covers the theoretical perspective of deep learning and machine learning.

Throughout this course, you will work on various quizzes. These quizzes will clear your concepts. Java will be used in this course for Programming.

Profs. Charles Isbell and Michael Littman will be your instructors. Both are experts in the field of Deep Learning.

Extra Benefits-

• For this course, you don’t need to pay any money.

Drawbacks-

• You will not receive a certificate after completing this FREE course.

Best For-

• Those who have a previous understanding of Machine Learning Algorithms and Java Programming.

Interested to Enroll?

If yes, then check it out here– Reinforcement Learning

3. Deep Learning and Reinforcement Learning- Coursera

Rating-	4.7/5
Time to Complete-	14 hours
Paid/FREE-	Paid
Programming Language Used-	Python

This Deep Learning and Reinforcement Learning course is available on Coursera and offered by IBM. Throughout this course, you will understand the theoretical concepts of Deep Learning and Reinforcement Learning.

This course begins with the Deep Learning basics and covers essential deep learning algorithms. You will also learn Convolutional Neural Networks, Recursive Neural Networks (RNNs), Long-Short Term Memory Networks (LSTM), and Autoencoders.

At the end of this course, you will learn about GAN and Reinforcement Learning.

Extra Benefits-

• You will get a Shareable Certificate.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Drawbacks-

• This course doesn’t cover Reinforcement Learning in detail. The reinforcement Learning topic was covered at the end and in very short.

Best For-

• Those who have previously worked on Python Programming and have knowledge of Data Cleaning, Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Calculus, Linear Algebra, Probability, and Statistics.

Interested to Enroll?

If yes, then check it out here– Deep Learning and Reinforcement Learning

4. Reinforcement Learning beginner to master – AI in Python- Udemy

Rating-	4.8/5
Time to Complete-	10.5 hours
Paid/FREE-	Paid
Programming Language Used-	Python

Reinforcement Learning beginner to master – AI in Python name sound like it is for beginners but to understand the concepts, you must have previous knowledge of Python and a basic understanding of linear algebra, calculus, statistics, and probability theory.

But this course will teach you Deep Reinforcement Learning basics and the instructor of this course help you to understand the concepts with the help of examples.

In short, this course is the perfect mixture of theory and practice. If you know python and the basic maths required for Machine Learning, you can go for this course.

Extra Benefits-

• You will get a Certificate of Completion.
• You will also get 19 articles and 1 downloadable resource.
• Along with that, you will get lifetime access to the course material.

Drawback-

• The quality of the videos could be improved.

Best For-

• Those who can program in Python and know basic linear algebra, calculus, statistics, and probability theory.

Interested to Enroll?

If yes, then check it out here– Reinforcement Learning beginner to master – AI in Python

5. AWS Machine Learning Foundations Course- Udacity

Rating-	NA
Time to Complete-	2 months
Paid/FREE-	FREE
Programming Language Used-	Python

This AWS Machine Learning Foundations Course is a completely FREE course. This is not basically a complete deep reinforcement learning course, but some concepts of reinforcement learning are covered.

During this course, you will understand the working of reinforcement learning in the context of AWS DeepRacer.

This course is to learn advanced topics of machine learning and to understand AWS AI Devices such as AWS DeepRacer and AWS DeepComposer.

Software Engineering and Object-Oriented Programming topics will be also covered in this course.

Extra Benefits-

• The course is completely FREE.

Drawbacks-

• You will not receive a certificate of completion in this course.

Best For-

• Those who have basic Python understanding.

Interested to Enroll?

If yes, then check it out here–AWS Machine Learning Foundations Course

6. Tensorflow 2.0: Deep Learning and Artificial Intelligence– Udemy

Rating-	4.7/5
Time to Complete-	21 hours
Paid/FREE-	Paid
Programming Language Used-	Python

This Tensorflow 2.0: Deep Learning and Artificial Intelligence course is for beginner-level students. This course is good for you if you want to learn Deep Learning Basics such as Neural networks, CNN, RNN, FeedForward Artificial Neural networks, etc.

The course begins with covering these Deep Learning topics and after that instructor covers the theory of deep reinforcement learning and one project, “Stock Trading Project with Deep Reinforcement Learning”.

You will also work on some other projects in this course-

• Natural Language Processing (NLP)
• Recommender Systems
• Transfer Learning for Computer Vision
• Generative Adversarial Networks (GANs)
• Deep Reinforcement Learning Stock Trading Bot

Extra Benefits-

• You will get a Certificate of Completion.
• Along with that, you will get lifetime access to the course material.

Drawbacks-

• The course only focuses on Theory.
• The explanation is not as good as compared to other courses.

Best For-

• Those who are beginners and want to learn about deep learning and AI in Tensorflow 2.0.

Interested to Enroll?

If yes, then check out all details here-Tensorflow 2.0: Deep Learning and Artificial Intelligence.

7. Machine Learning for Trading Specialization– Coursera

Rating-	3.9/5
Time to Complete-	3 months ( If you spend 4 hours per week)
Paid/FREE-	Paid
Programming Language Used-	Python

This Machine Learning for Trading Specialization course is all about Trading using Machine Learning. First, you will learn what is Trading and how Trading can be performed using Machine Learning.

This course is offered by Google Cloud that’s why you will learn how to use the Google Cloud Platform for building ML models.

After teaching various trading strategies such as quantitative trading, pairs trading, and momentum trading, you will learn reinforcement learning basics.

This is a specialization program and has 3 courses-

1. Introduction to Trading, Machine Learning & GCP
2. Using Machine Learning in Trading and Finance
3. Reinforcement Learning for Trading Strategies

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Drawbacks-

• The program doesn’t cover Deep Reinforcement learning in detail.
• In terms of Deep Reinforcement learning, this is an introductory level course.

Best For-

• Those who have basic knowledge in Python programming and familiarity with the Scikit Learn, Statsmodels, and Pandas library.
• And those who have a background in statistics and foundational knowledge of financial markets.

Interested to Enroll?

If yes, then check it out here– Machine Learning for Trading Specialization

8. AWS DeepRacer- Udacity

Rating-	NA
Time to Complete-	2 weeks
Paid/FREE-	FREE
Programming Language Used-	Python

This AWS DeepRacer is another completely FREE course related to Reinforcement learning. This course is offered by AWS. In this course, you will learn about AWS DeepRacer.

AWS DeepRacer is a Machine Learning Project. The main focus of AWS DeepRacer is the development of autonomous racing vehicles on a small scale.

You will learn the processing of reinforcement learning models in the AWS DeepRacer 3D racing simulator.

Extra Benefits-

• The course is completely FREE.

Drawbacks-

• You will not receive a certificate of completion in this course.

Best For-

• Those who have previously worked in Python Programming.

Interested to Enroll?

If yes, then check it out here– AWS DeepRacer

9. Practical AI with Python and Reinforcement Learning- Udemy

Rating-	4.8/5
Time to Complete-	26.5 hours
Paid/FREE-	Paid
Programming Language Used-	Python

This Practical AI with Python and Reinforcement Learning course will cover the core concepts of Reinforcement learning. The best part about this course is that you will learn the math required for reinforcement learning.

The instructor explains each topic very easily and you will understand the complex topics easily.

Throughout this course, you will also learn OpenAI Gym, Classical Q-Learning, Deep Q-Learning, etc. The instructor will teach TensorFlow and Keras frameworks.

Extra Benefits-

• You will get a Certificate of Completion.
• You will also get 6 articles and 9 downloadable resources.
• Along with that, you will get lifetime access to the course material.

Drawbacks-

• The course doesn’t cover Reinforcement Learning theory in detail.

Best For-

• Those who are comfortable with basic Python and installing Python libraries.

Interested to Enroll?

If yes, then check it out here– Practical AI with Python and Reinforcement Learning

10. Deep Reinforcement Learning 2.0- Udemy

Rating-	4.5/5
Time to Complete-	9.5 hours
Paid/FREE-	Paid
Programming Language Used-	Python

This Deep Reinforcement Learning 2.0 is the last course on this list of Deep Reinforcement Learning courses.

To understand the Deep Reinforcement Learning concepts, you must have some previous knowledge of Deep Reinforcement Learning fundamentals.

This course will cover Reinforcement Learning, the Bellman Equation, Markov Decision Process, Policy vs Plan, etc.

Extra Benefits-

• You will get a Certificate of Completion.
• You will also get 7 articles and 1 downloadable resource.
• Along with that, you will get lifetime access to the course material.

Drawbacks-

• The explanation of the concepts is not up to the mark.

Best For-

• Those who know some maths basics and a bit of programming knowledge.

Interested to Enroll?

If yes, then check it out here– Deep Reinforcement Learning 2.0

And here the list ends. I hope these Best Deep Reinforcement Learning Courses will help you. I would suggest you bookmark this article for future referrals.

Comparison of Best Deep Reinforcement Learning Courses

S/N	Course Name	FREE/Paid	Time to Complete	Drawbacks
1.	Become a Deep Reinforcement Learning Expert– Udacity	Paid	4 months (If you spend 10 hours per week)	Expensive
2.	Reinforcement Learning– Udacity	FREE	4 Months	Doesn’t Provide a Certificate
3.	Deep Learning and Reinforcement Learning– Coursera	Paid	14 hours	Basic Topic Coverage in terms of Deep Reinforcement Learning.
4.	Reinforcement Learning beginner to master – AI in Python– Udemy	Paid	10.5 hours	The quality of the Videos is not up to the mark.
5.	AWS Machine Learning Foundations Course– Udacity	FREE	2 months	Doesn’t Provide a Certificate
6.	Tensorflow 2.0: Deep Learning and Artificial Intelligence– Udemy	Paid	21 hours	Only covers theory.
7.	Machine Learning for Trading Specialization– Coursera	Paid	3 months ( If you spend 4 hours per week)	Doesn’t cover Deep Reinforcement learning in detail.
8.	AWS DeepRacer– Udacity	FREE	2 weeks	Doesn’t Provide a Certificate
9.	Practical AI with Python and Reinforcement Learning– Udemy	Paid	26.5 hours	Doesn’t cover Reinforcement Learning theory in detail.
10.	Deep Reinforcement Learning 2.0– Udemy	Paid	9.5 hours	The instructor’s explanation is not up to the mark.

FAQ on Deep Reinforcement Learning Course

Now it’s time to wrap up.

Conclusion

In this article, I tried to cover the 10 Best Deep Reinforcement Learning Courses. If you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

Thank YOU!

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Though of the Day…

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– Henry Ford