9 Best Online Reinforcement Learning Courses & Certification of 2023

Students with so many Reinforcement Learning find it incredibly hard to meet their requirements. Learners frequently ask if there is a Reinforcement Learning for each case. The answer is YES. You can find popular courses below. For your career development, registering for the right course is a significant consideration. The best courses and classes in the Reinforcement Learning were selected by hand in this article in 2023.

Our main objective is to illustrate the best known and famous courses in each category.

Based on your choice, you choose the one that best suits your needs.

Let’s, however, look at the best Reinforcement Learning courses on the market.

1. Reinforcement Learning Specialization (Coursera)

Duration: Self-paced

Rating: 4.7 out of 5

This specialization course consists of four courses offered by the University of Alberta to help you explore the power of adaptive learning systems and artificial intelligence. This program will show how reinforcement learning solutions can help you to solve real problems through the interaction of trial and mistakes by implementing a complete RL solution from start to finish. The program is designed by the University of Alberta’s experienced faculty so that you are in direct contact with the lecturers to answer your queries. You will also have a clear understanding of modern probabilistic artificial intelligence after the specialization.

Key Highlights:

• Know how to develop a sequential decision making enhancement system to resolve real-world problems.
• Understand how you can formalize tasks as a learning problem and how a solution can be quickly implemented.
• A comprehensive curriculum that will guide you to the most basic and advanced concepts of artificial intelligence enhancement learning.
• Be able to move on to more advanced automation issues after this specialisation.
• Read more about RL algorithms, including Monte-Carlo, Policy Gradients, Sarsa, Q-learning, Dyna, and more.

You can Sign up Here

2. Become a Deep Reinforcement Learning Expert – Nanodegree (Udacity)

Duration: 4 months, 10-15hrs/week

Rating: 4.5 out of 5

This nanodegree program is designed by expert teachers from Udacity and helps you learn the deep reinforcement learning skills that support the progress in AI. This program helps you how to write your own implementations for state-of-the-art algorithms like DQN, DDPG and evolutionary methods. In addition, you can also learn how to use reinforcement learning approaches for systems involving multiple interacting entities, for example. The curriculum consists of different real-world projects, hands-on activities, graded tasks and rich learning content, so you can better understand the topics. If the course is successful, you earn a completion certificate that can be used to demonstrate your skills. Don’t forget to look at our best Space Data Courses list.

Key Highlights:

• Understand the theory behind evolutionary algorithms and policy gradient methods for the development of your own robotic arm simulator algorithm.
• Personal job counselling, preparatory interviews and resume software, GitHub reviews and a profile analysis on LinkedIn after the course has finished.
• Learn the basic concepts of improved learning and how to use it to develop the architecture for reinforcement learning.
• Get support and guidance from expert mentors who work to answer questions, motivate and track you.

You can Sign up Here

3. Reinforcement Learning Explained (edX)

Duration: 6 weeks, 4-8 hours/week

Rating: 4.6 out of 5

If you’re new to reinforcement learning, you might get an excellent opportunity to learn more about this course. In this program, you will learn how to limit reinforcement learning problems and address classic examples, such as trying to balance a cart pole, news advice and trying to learn to navigate a grid world. This course is part of a technical AI certification program that allows you to proceed with advanced AI concepts to broaden your knowledge after completing this course. You will also obtain a completion certificate after the course is finished.

Key Highlights:

• Explore fundamental algorithms from multi-armed robbers, dynamic programming, and time difference analysis using function approximation.
• Learn the algorithms that are designed to find the right policy with political gradients and actor-critical methods.
• Learn how to handle improvements, decision-making, robbers, complex programming and much more.
• Avail financial help from edX if the financial stability is not available to obtain verified certificates associated with this course.
• Introduce Project Malmo which is a great and useful platform for experiments and research on artificial intelligence.

You can Sign up Here

4. Reinforcement Learning in Python (Udemy)

Duration: 9-10 hours

Rating: 4.6 out of 5

People wishing to master artificial intelligence through deep thinking and methods of enhancement will take advantage of this course. This course will lead you to all aspects of artificial intelligence with supervised and unattended machine learning algorithms. You should understand how the method of improving learning is completely different from directed and unregulated learning. The course instructor, Lazy Programmer, is an accomplished artificial engineer who will support you during your study. It will enable you to build profound models to predict click rate and user actions while providing an overview of various artificial intelligence concepts.

Key Highlights:

• Take up the main subjects of enhancement learning such as decision-making, complex programming, Monte Carlo, temporary differences and many others.
• Read from AI strategies you’ve never seen before in traditionally supervised learning or deep learning.
• Learn about various ways to measure averages and movements and their relationship with stochastic downward gradient.
• Freedom to test with a 30 days free trial from your comfort zone.
• Consider the connection between enhancement and psychology
• Learn how to implement 17 different reinforcement learning algorithms and understand enhancement technology

You can Sign up Here

5. Deep Reinforcement Learning in Python (Udemy)

Duration: 8-9 hours

Rating: 4.6 out of 5

Reinforcement learning is just another part of artificial intelligence, much more than such as profound learning, neural networks, etc. This Udemy course teaches you all about the application of profound thinking, neural networks to Reinforcement learning. In this course you will learn how Reinforcement learning is completely different from supervised and unsupervised learning. You will learn how supervised and unsupervised machine-learning algorithms can be used to analyze and predict data, but enhanced learning can be used to train agents to communicate with and maximize their reward. You will be awarded a certificate of completion from Udemy at the end of the course.

Key Highlights:

• Learn how to construct different deep learning agents like DQN, A3C, etc by means of reinforcement learning methods.
• A complete guide to artificial intelligence learning and mastering using deep learning and neural networks.
• Learn how to use a range of deep learning algorithms to solve any complex problem.
• Get access to several videos, practical exercises and tests to improve your skills and knowledge.
• Understand the use of neural networks with profound Q-learning and policy gradient methods with neural networks

You can Sign up Here

6. Reinforcement Learning by Georgia Tech (Udacity)

Duration: 4 months

Rating: 4.5 out of 5

If you belong to those who want free courses to continue with strengthening training, this is the platform that’s right for you. Udacity provides Georgia Tech ‘s intensive free enhancement learning. In this course you will discuss automated decision-making, analyze efficient algorithms, where they operate, in single agent and multi-agent planning and many other topics from a computer science point of view. This is an advanced machine course with a rich content which helps you learn easily and efficiently. You can even enroll in the deep strengthening training offered by a Nano degree programme, after completing this course.

Key Highlights:

• Activate your field knowledge with educational videos, interactive tests and external resources.
• Prepare to be part of the reinforcement learning research community after finishing this course.
• Get a chance to learn from two of the leading experts in strengthening learning.
• A system of self-learning with freedom to study at home.
• Enter the student community to connect with and learn from other people who adopt this course.

You can Sign up Here

7. Practical Reinforcement Learning (Coursera)

Duration: 6 weeks, 4-5 hours/week

Rating: 4.1 out of 5

It is one of the best courses in education for Reinforcement learning. You’ll be introduced to basic RL methods such as value / political iteration, Q-learning, policy gradient, etc. The course is offered as part of the Advanced Machine Learning program by the National Research University Higher School of Economics. You should then participate in advanced machine learning courses in order to increase the expertise at the end of this course. This course includes multiple video lectures, exercises, questionnaires and external resources so that you can analysis your know-how and develop your skills at every stage of your learning.

Key Highlights:

• Know the state of the art RL algorithms and how to apply the duct tape in practical situations.
• An initial and an extensive course designed to offer you all the knowledge of machine learning reinforcement.
• Learn how to use deep neural networks to solve problems in Reinforcement networks.
• Earn an achievement certificate to show off your skills with employers through your LinkedIn profile.
• Get ongoing support from a team of experts and instructors to help with any course-related questions

You can Sign up Here

8. Reinforcement Learning (Stanford Education)

Duration: 2 months, 2-3 hours/week

Rating: 4.5 out of 5

Individuals who want to learn how to make the right decisions using artificial intelligence can help with this efficient Stanford University course. This course gives you a strong insight into the field of Reinforcement learning and the main problems and strategies used in Reinforcement learning, such as exploration or generalisation. This course contains a mix of lectures and written coding tasks to help you learn key ideas and techniques for RL. You shall be assigned at the end of the course to work on an actual project to analyze your skills and learning.

Key Highlights:

• Understand how to define which algorithms are best suited for RL problems and justify your response.
• Learn how to define key Reinforcement learning features that differentiate AI from non-interactive machine learning.
• Learn how to solve complex RL problems by determining whether or not to formulate them as an RL problem.
• Get access to tasks, quizzes, video lectures and much more with every course class.
• Read about multiple criteria for RL analysis and how algorithms such as sample complexity, empirical performance, regret, etc can be evaluated on these metrics.

You can Sign up Here

9. Reinforcement Learning Courses (Udemy)

Duration: Self-paced

Rating: 4.5 out of 5

If you are confused as to where to start refresher learning or what are the best refresher learning courses, don’t waste your time. Udemy provides a list of different courses and tutorials on the enhancement from various colleges and universities. If you want to know about the fundamentals of improving learning or highly advanced topics, Udemy has a course for you. Nevertheless, the bestsellers of these courses include Artificial Intelligence: Reinforcement Learning in Python, Deep Reinforcement Learning 2.0, and Reinforcement Learning with PyTorch. Completing these courses will help you to develop your career in this area better with all the skills you need.

Key Highlights:

• Each course is offered by an experienced teacher or institution who will help you in every phase of learning.
• A list of effective and useful reinforcement learning courses covering the basics and advanced subjects of AI.
• Read about Artificial Intelligence and how to use  reinforcement learning in various languages such as Java, Python, etc.
• Most of the courses include video tutorials, questionnaires, rich learning contents and activities to help you develop your abilities.
• Get support for all queries relating to the course material or timetable from an expert team.

You can Sign up Here

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Wrapping Up

This is the list of the 9 Best Online Reinforcement Learning Courses & Certification of 2023. They are popular and loved by many data scientists. You will find between these courses what you need to learn in order to continue your machine learning path.