5 Best Reinforcement Learning Courses
5 Best Reinforcement Learning Courses
In this article, take a look at five of the best reinforcement learning courses.
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A team of global experts compiled this list of best reinforcement courses, classes, tutorials, training, and certification programs available online. This list includes both free and paid courses to help you learn reinforcement learning. Also, it is ideal for beginners, intermediates, and experts.
5 Best Reinforcement Learning Courses and Certifications
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.
- 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
Rating: 4.7 out of 5
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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.
- 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
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.
- 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
Review: I have always liked teaching style by Lazy programmer, and it's helping me in my nonlinear journey to deep learning. - Shruti Kulkarni
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.
- 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
Review: Great Basic course with plenty of examples and great exposition of the main ideas. - Zhivkov Kolev
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.
- 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
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 :)
Published at DZone with permission of Karen Gracias . See the original article here.
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