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8 Best Reinforcement Learning Courses

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Here are some of the Best Reinforcement Coursesavailable online for 2019. This list includes both free and paid courses to help you learn Reinforcement. Also, it is ideal for beginners, intermediates, and experts.


8 Best Reinforcement Learning Courses & Certification [2019]

1. Explained Reinforcement Learning - Free Course (edX)

If you are entirely new to reinforcement learning, then enrolling in this course could be an excellent opportunity for you to learn all about it. In this program, you will get introduced to the world of reinforcement learning while learning how to border reinforcement learning problems and tackle classic examples, such as balancing a cart-pole, news recommendation, and learning to navigate in a grid-world. This course is a part of a professional AI certification program, which means after finishing this course, you can move on to other advanced concepts of AI to expand your knowledge. Also, you will receive a certificate of completion after completing the course.


Key USPs –

  • Learn how to tackle reinforcement learning problems, Markov decision process, Bandits, Dynamic Programming, and much more

  • Explore the basic algorithms from multi-armed bandits, dynamic programming, and temporal difference learning using function approximation

  • Learn the algorithms that focus on finding the best policy with policy gradient and actor-critic methods

  • Get introduced to Project Malmo that is a great and useful platform for artificial intelligence experimentation and research

  • Avail financial assistance from edX if you don’t have the financial stability to earn the verified certificates associated with this course


Duration: 6 weeks, 4-8 hours/week

Rating: 4.6 out of 5

You can Sign up Here


2. Reinforcement Learning Specialization (Coursera)

Offered by the University of Alberta, this reinforcement learning specialization program consists of four different courses that will help you explore the power of adaptive learning systems and artificial intelligence. In this program, you will learn how reinforcement learning solutions can help you solve real-world problems via trial-and-error interaction by implementing a complete RL solution from beginning to end. The program is designed by the experienced faculty of the University of Alberta, so you will be in direct touch with the instructors to resolve your queries. Also, after finishing the specialization, you will have a clear understanding of modern probabilistic artificial intelligence.


Key USPs –

  • A comprehensive course that is created to guide you to the most basics as well as advanced concepts of Reinforcement learning related to artificial intelligence

  • Learn how to build a reinforcement learning system for sequential decision making and to solve real-world problems

  • Understand how you can formalize tasks as a reinforcement learning problem, and how a solution can be implemented with it quickly

  • Learn about the space of RL algorithms, such as Monte Carlo, Policy Gradients, Sarsa, Q-learning, Dyna, and much more

  • Be able to move to more advanced topics of artificial intelligence after completing this specialization program


Duration: Self-paced

Rating: 4.7 out of 5

You can Sign up Here



3. Deep Reinforcement Learning in Python (Udemy)

Reinforcement Learning is just another part of artificial intelligence; there is much more than that like deep learning, neural networks, etc. This course from Udemy will teach you all about the application of deep learning, neural networks to reinforcement learning. In this course, you will learn how reinforcement learning is entirely a different kind of machine learning as compared to supervised and unsupervised learning. You will learn how supervised, and unsupervised machine learning algorithms can be used for analyzing and making predictions about data, but reinforcement learning can be used to train an agent to interact with an environment and maximize its reward. At the end of the course, you will be rewarded with a certificate of completion from Udemy.


Key USPs –

  • A comprehensive guide to learn and master artificial intelligence with Deep learning and neural networks

  • Learn how to build various deep learning agents, such as DQN, A3C, etc. with the help of reinforcement learning methods

  • Learn how to apply a variety of advanced reinforcement learning algorithms to resolve any complex problem

  • Understand the use of convolutional neural networks with Deep Q-learning and policy gradient methods with Neural networks

  • Get access to multiple videos, practical exercises, and quizzes to improve your knowledge and skills


Duration: 8-9 hours

Rating: 4.6 out of 5

You can Sign up Here


Review: I have always liked teaching style by Lazy programmer, and it's helping me in my nonlinear journey to deep learning. - Shruti Kulkarni



4. Reinforcement Learning in Python (Udemy)

Individuals who want to learn artificial intelligence with deep learning and reinforcement learning methods can take help from this course. This course will guide you to every aspect of artificial intelligence included with supervised and unsupervised machine learning algorithms. You will learn how the reinforcement learning paradigm is completely different than supervised and unsupervised learning. The instructor of the course, Lazy Programmer, is an experienced artificial engineer who will assist you at every stage of learning. He will help you learn how to create deep learning models to predict click-through rate and user behavior while providing an overview of different concepts of artificial intelligence.


Key USPs –

  • Cover the essential topics included in reinforcement learning, such as Markov decision process, dynamic programming, Monte Carlo, Temporal difference learning, and many more

  • Learn about AI techniques that you have never seen before in traditional supervised machine learning or deep learning

  • Know about various ways to calculate means and moving averages and their relationship with stochastic gradient descent

  • Understand the relationship between reinforcement learning and psychology

  • Learn how to implement 17 different reinforcement learning algorithms, and understand reinforcement learning on a technical level

  • Liberty to study from your comfort zone with a 30 days free trial


Duration: 9-10 hours

Rating: 4.6 out of 5

You can Sign up Here


Review: Great Basic course with plenty of examples and great exposition of the main ideas. - Zhivkov Kolev



5. Practical Reinforcement Learning (Coursera)

This is one of the best courses on Reinforcement learning with a practical approach. In this course, you will be introduced to the foundation of RL methods, such as value/policy iteration, Q-learning, policy gradient, and many more. This course is offered by the National Research University Higher School of Economics as a part of the Advanced Machine Learning Specialization program. So, on completion of this course, you can enroll yourself in advanced courses of machine learning to expand your knowledge. This course is included with multiple video lectures, practice exams, quizzes, and external resources so that you can analyze your expertise at every stage of learning and expand your skills.


Key USPs –

-  An introductory as well as a comprehensive course that is designed to provide you with all the knowledge of Reinforcement Learning in machine learning

  • Learn how to use deep learning neural networks to resolve reinforcement learning problems

  • Know about the state of the art RL algorithms and how to apply duct tape to them for practical problems

  • Get continuous support from a team of experts as well as guidance form the instructors for any queries related to the course

  • Receive a certificate of completion that can be shared with employers or your LinkedIn profile to showcase your skills


Duration: 6 weeks, 4-5 hours/week

Rating: 4.1 out of 5

You can Sign up Here


Review: This is one of the Best Course available on Reinforcement Learning. I have gone through various study material, but the depth and practical knowledge is given in the course are awesome.



6. Reinforcement Learning by Georgia Tech (Udacity)

If you are among those individuals who are looking for free courses to begin with reinforcement learning, then this is the right platform for you. Udacity offers a comprehensive free reinforcement learning course that is created by Georgia Tech. In this course, you will get to explore automated decision-making from a computer-science perspective, you will examine efficient algorithms, where they exist, for single-agent and multi-agent planning, and many other concepts. It is an advanced level machine course included with rich learning content that helps you learn in a simple and efficient manner. After completing this course, you can even enroll yourself in deep reinforcement learning that is a Nano degree program offered by unity.


Key USPs –

  • Prepare yourself to participate in the reinforcement learning research community after finishing this course

  • Get the opportunity to learn from two of the foremost experts in the field of reinforcement learning

  • Get access to instructional videos, interactive quizzes, and external resources to expand your knowledge in the field

-  Join the student t support community to interact with other individuals who are taking this course and learning from it

  • A self-learning programming with the freedom to study from the comfort of your home


Duration: 4 months

Rating: 4.5 out of 5

You can Sign up Here



7. Reinforcement Learning Courses (Udemy)

If you’re confused about where to begin with Reinforcement learning courses, or what are the best reinforcement learning courses, then don’t waste your time anymore. Udemy is offering a list of various Reinforcement courses and tutorials from different institutions and universities. Whether you want to get introduced to the basics of Reinforcement learning or learn the highly advanced concepts of Deep Reinforcement Learning, Udemy has a course for you. However, amongst these courses, the bestsellers are Artificial Intelligence: Reinforcement Learning in Python, Deep Reinforcement Learning 2.0, and Reinforcement Learning with PyTorch. Completing these courses will help you better equipped with all the necessary skills that you need to grow your career in this field.


Key USPs –

  • A list of effective and useful reinforcement learning courses that cover the basics as well as advanced topics of AI

  • Learn about Artificial Intelligence and how to use reinforcement learning in various programming languages, such as Java, Python, etc.

  • Each course is provided by an experienced instructor or institution, who will assist you at every stage of learning

  • Get support from a team of experts for any queries related to the course material or schedule

  • Most of the courses are included with video lectures, quizzes, rich learning content, and practice exams to help you improve your skills


Duration: Self-paced

Rating: 4.5 out of 5

You can Sign up Here



8. Reinforcement Learning Winter (Stanford Education)

Individuals who want to learn how to make use of Artificial intelligence to make the right decisions can take help from this efficient Reinforcement Learning course provided by Stanford University. This course will give you a solid introduction to the field of reinforcement learning and the core challenges and approaches included in Reinforcement learning, such as exploration or generalization. This course consists of a combination of lectures and written coding assignments to help you become well-versed with key ideas and techniques for RL. At the end of the course, you will be assigned to work on a real-world project to analyze your skills and learning.


Key USPs –

  • Learn how to define the key features of reinforcement learning that differentiate it from AI and non-interactive machine learning

  • Learn to solve complicated RL problems by deciding whether they should be formulated as an RL problem or not

  • Understand how to define what algorithms are best suited for addressing RL problems and justify your answer for it

  • Learn about multiple criteria for analyzing RL algorithms and how to evaluate algorithms on these metrics like sample complexity, empirical performance, regret, etc.

  • Get access to assignments, quizzes, video lectures, and much more with every class of the course


Duration: 2 months, 2-3 hours/week

Rating: 4.5 out of 5

You can Sign up Here


Those were some of the best reinforcement learning courses, certifications and training available online. Hope you found some relevant courses to help you grow in your career :)

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