8 Best Reinforcement Learning Courses
Tags: machinelearning, datascience, tutorial, ai
Published: 2019-11-26 15:08:01

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

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<h2>8 Best Reinforcement Learning Courses &amp; Certification [2019]</h2>

<h3><strong>1. <a href="https://www.awin1.com/cread.php?awinmid=6798&amp;awinaffid=427859&amp;clickref=ddreinforcementlearning2&amp;p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Freinforcement-learning-explained%5D%5D" target="_blank" rel="nofollow noopener">Explained Reinforcement Learning - Free Course (edX)</a></strong></h3>
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 <strong>get introduced to the world of reinforcement learning while learning how to border reinforcement learning problems and tackle classic examples</strong>, 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 <strong>move on to other advanced concepts of AI to expand your knowledge</strong>. Also, you will receive a certificate of completion after completing the course.

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<strong>Key USPs –</strong>

- 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

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<strong>Duration: 6 weeks, 4-8 hours/week</strong>

<strong>Rating: 4.6 out of 5</strong>

<strong>You can <a href="https://www.awin1.com/cread.php?awinmid=6798&amp;awinaffid=427859&amp;clickref=ddreinforcementlearning2&amp;p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Freinforcement-learning-explained%5D%5D" target="_blank" rel="nofollow noopener">Sign up Here</a></strong>

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<h3><strong>2. <a href="https://click.linksynergy.com/deeplink?id=vedj0cWlu2Y&amp;mid=40328&amp;u1=ddreinforcementlearning1&amp;murl=https%3A%2F%2Fwww.coursera.org%2Fspecializations%2Freinforcement-learning" target="_blank" rel="nofollow noopener">Reinforcement Learning Specialization (Coursera)</a></strong></h3>
Offered by the University of Alberta, this reinforcement learning specialization program <strong>consists of four different courses that will help you explore the power of adaptive learning systems and <a href="https://digitaldefynd.com/best-artificial-intelligence-courses-training-certifications/?wsreinforcementlearning" target="_blank" rel="noopener">artificial intelligence</a></strong>. 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 <strong>be in direct touch with the instructors to resolve your queries</strong>. Also, after finishing the specialization, you will have a clear understanding of modern probabilistic artificial intelligence.

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<strong>Key USPs – </strong>

- 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

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<strong>Duration: Self-paced</strong>

<strong>Rating: 4.7 out of 5</strong>

<strong>You can <a href="https://click.linksynergy.com/deeplink?id=vedj0cWlu2Y&amp;mid=40328&amp;u1=ddreinforcementlearning1&amp;murl=https%3A%2F%2Fwww.coursera.org%2Fspecializations%2Freinforcement-learning" target="_blank" rel="nofollow noopener">Sign up Here</a></strong>

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<h3><strong>3. <a href="https://click.linksynergy.com/deeplink?id=vedj0cWlu2Y&amp;mid=39197&amp;u1=ddreinforcementlearning3&amp;murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fdeep-reinforcement-learning-in-python%2F" target="_blank" rel="nofollow noopener">Deep Reinforcement Learning in Python (Udemy)</a></strong></h3>
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 <strong>teach you all about the application of deep learning, neural networks to reinforcement learning</strong>. In this course, you will learn how reinforcement learning is entirely a different kind of <a href="https://digitaldefynd.com/best-machine-learning-and-deep-learning-courses/?wsreinforcementlearning" target="_blank" rel="noopener">machine learning</a> as compared to supervised and unsupervised learning. You will <strong>learn how supervised, and unsupervised machine learning algorithms can be used for analyzing and making predictions about data</strong>, 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.

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<strong>Key USPs – </strong>

- 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

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<strong>Duration: 8-9 hours</strong>

<strong>Rating: 4.6 out of 5</strong>

<strong>You can <a href="https://click.linksynergy.com/deeplink?id=vedj0cWlu2Y&amp;mid=39197&amp;u1=ddreinforcementlearning3&amp;murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fdeep-reinforcement-learning-in-python%2F" target="_blank" rel="nofollow noopener">Sign up Here</a></strong>

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<blockquote>Review: I have always liked teaching style by Lazy programmer, and it's helping me in my nonlinear journey to deep learning. - Shruti Kulkarni</blockquote>
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<h3><strong>4. <a href="https://click.linksynergy.com/deeplink?id=vedj0cWlu2Y&amp;mid=39197&amp;u1=ddreinforcementlearning4&amp;murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fartificial-intelligence-reinforcement-learning-in-python%2F" target="_blank" rel="nofollow noopener">Reinforcement Learning in Python (Udemy)</a></strong></h3>
Individuals who want to learn artificial intelligence with deep learning and reinforcement learning methods can take help from this course. This course will <strong>guide you to every aspect of artificial intelligence included with supervised and unsupervised machine learning algorithms</strong>. You will learn how the reinforcement learning paradigm is completely different than supervised and unsupervised learning. The <strong>instructor of the course, Lazy Programmer, is an experienced artificial engineer who will assist you at every stage of learning</strong>. 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.

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<strong>Key USPs –</strong>

- 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

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<strong>Duration: 9-10 hours</strong>

<strong>Rating: 4.6 out of 5</strong>

<strong>You can <a href="https://click.linksynergy.com/deeplink?id=vedj0cWlu2Y&amp;mid=39197&amp;u1=ddreinforcementlearning4&amp;murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fartificial-intelligence-reinforcement-learning-in-python%2F" target="_blank" rel="nofollow noopener">Sign up Here</a></strong>

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<blockquote>Review: Great Basic course with plenty of examples and great exposition of the main ideas. - Zhivkov Kolev</blockquote>
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<h3><strong>5. <a href="https://click.linksynergy.com/deeplink?id=vedj0cWlu2Y&amp;mid=40328&amp;u1=ddreinforcementlearning5&amp;murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fpractical-rl" target="_blank" rel="nofollow noopener">Practical Reinforcement Learning (Coursera)</a></strong></h3>
This is one of the best courses on Reinforcement learning with a practical approach. In this course, you will be <strong>introduced to the foundation of RL methods, such as value/policy iteration, Q-learning, policy gradient, and many more</strong>. 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 <strong>enroll yourself in advanced courses of machine learning to expand your knowledge</strong>. 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.

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<strong>Key USPs – </strong>

-  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

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<strong>Duration: 6 weeks, 4-5 hours/week</strong>

<strong>Rating: 4.1 out of 5</strong>

<strong>You can <a href="https://click.linksynergy.com/deeplink?id=vedj0cWlu2Y&amp;mid=40328&amp;u1=ddreinforcementlearning5&amp;murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fpractical-rl" target="_blank" rel="nofollow noopener">Sign up Here</a></strong>

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<blockquote>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.</blockquote>
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<h3><strong>6. <a href="http://www.anrdoezrs.net/links/7964208/type/dlg/sid/ddreinforcementlearning/https://www.udacity.com/course/reinforcement-learning--ud600" target="_blank" rel="nofollow noopener">Reinforcement Learning by Georgia Tech (Udacity)</a></strong></h3>
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 <strong>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</strong>. 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.

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<strong>Key USPs – </strong>

- 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

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<strong>Duration: 4 months</strong>

<strong>Rating: 4.5 out of 5</strong>

<strong>You can <a href="http://www.anrdoezrs.net/links/7964208/type/dlg/sid/ddreinforcementlearning/https://www.udacity.com/course/reinforcement-learning--ud600" target="_blank" rel="nofollow noopener">Sign up Here</a></strong>

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<h3><strong>7. <a href="https://click.linksynergy.com/deeplink?id=vedj0cWlu2Y&amp;mid=39197&amp;u1=ddreinforcementlearning7&amp;murl=https%3A%2F%2Fwww.udemy.com%2Ftopic%2Freinforcement-learning%2F" target="_blank" rel="nofollow noopener">Reinforcement Learning Courses (Udemy)</a></strong></h3>
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 <strong>offering a list of various Reinforcement courses and tutorials from different institutions and universities</strong>. 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, <strong>the bestsellers are Artificial Intelligence: Reinforcement Learning in Python, Deep Reinforcement Learning 2.0, and Reinforcement Learning with PyTorch</strong>. Completing these courses will help you better equipped with all the necessary skills that you need to grow your career in this field.

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<strong>Key USPs – </strong>

- 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

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<strong>Duration: Self-paced</strong>

<strong>Rating: 4.5 out of 5</strong>

<strong>You can <a href="https://click.linksynergy.com/deeplink?id=vedj0cWlu2Y&amp;mid=39197&amp;u1=ddreinforcementlearning7&amp;murl=https%3A%2F%2Fwww.udemy.com%2Ftopic%2Freinforcement-learning%2F" target="_blank" rel="nofollow noopener">Sign up Here</a></strong>

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<h3><strong>8. <a href="http://web.stanford.edu/class/cs234/index.html" target="_blank" rel="nofollow noopener">Reinforcement Learning Winter (Stanford Education)</a></strong></h3>
Individuals who want to <strong>learn how to make use of Artificial intelligence to make the right decisions</strong> can take help from this efficient Reinforcement Learning course provided by Stanford University. This course will <strong>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</strong>. 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.

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<strong>Key USPs – </strong>

- 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

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<strong>Duration: 2 months, 2-3 hours/week</strong>

<strong>Rating: 4.5 out of 5</strong>

<strong>You can <a href="http://web.stanford.edu/class/cs234/index.html" target="_blank" rel="nofollow noopener">Sign up Here</a></strong>

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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 :)