Top 10 Reinforcement Learning in Python Courses to Take Up
Reinforcement learning is the most trending type of ML as it can solve a wide range of complex decision-making tasks
Nowadays, Deep Reinforcement Learning is one of the hottest topics in the Data Science community. The fast development of RL has resulted in the growing demand for easy-to-understand and convenient-to-use RL tools. In recent years, plenty of RL libraries have been developed. These libraries were designed to have all the necessary tools to both implement and test Reinforcement Learning models. Still, they differ quite a lot. That’s why it is important to pick a library that will be quick, reliable, and relevant for your RL task. The “deep” portion of reinforcement learning refers to multiple (deep) layers of artificial neural networks that replicate the structure of a human brain. This article features the top 10 reinforcement learning in Python courses to take up in 2022.
Advanced AI: Deep Reinforcement Learning in Python- Udemy
This course is all about the application of deep learning and neural networks to reinforcement learning. Specifically, the combination of deep learning with reinforcement learning has led to AlphaGo beating a world champion in the strategy game Go, it has led to self-driving cars, and it has led to machines that can play video games at a superhuman level.
Reinforcement Learning with Python- Great Learning
This free course starts by providing you with an introduction to Reinforcement Learning. You will get a brief understanding of what Reinforcement Learning is and what vital role it plays. You will learn and understand the framework of Reinforcement Learning. You will then learn about the model-free Reinforcement Learning algorithm called Q-learning. You will get in-depth knowledge of how it works and what output must be expected.
Artificial Intelligence: Reinforcement Learning in Python- Udemy
Reinforcement learning opens up a whole new world. As you’ll learn in this course, the reinforcement learning paradigm is very different from both supervised and unsupervised learning. It’s led to new and amazing insights both in behavioral psychology and neuroscience. As you’ll learn in this course, there are many analogous processes when it comes to teaching an agent and teaching an animal or even a human. It’s the closest thing we have so far to a true artificial general intelligence.
Cutting-Edge AI: Deep Reinforcement Learning in Python- Udemy
This course is going to show you a few different ways: including the powerful A2C (Advantage Actor-Critic) algorithm, the DDPG (Deep Deterministic Policy Gradient) algorithm, and evolution strategies. Evolution strategies are a new and fresh take on reinforcement learning, that kind of throws away all the old theories in favor of a more “black box” approach, inspired by biological evolution.
Reinforcement Learning Specialization- Coursera
The Reinforcement Learning Specialization consists of 4 courses exploring the power of adaptive learning systems and artificial intelligence (AI). Harnessing the full potential of artificial intelligence requires adaptive learning systems. Learn how Reinforcement Learning (RL) solutions help solve real-world problems through trial-and-error interaction by implementing a complete RL solution from beginning to end.
Machine Learning with Python: from Linear Models to Deep Learning- edX
This course provides an in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. You will understand the principles behind machine learning problems such as classification, regression, clustering, and reinforcement learning. Also, you will be able to implement and analyze models such as linear models, kernel machines, neural networks, and graphical models.
Deep Learning on Azure with Python: Reinforcement Learning- Future Learn
This machine learning course focuses on reinforcement learning and how it uses artificial intelligence to find the best possible solution to complex problems involving multiple decisions. Discover reinforcement learning in this course covering how to frame reinforcement learning problems, algorithms, and more.
Practical Reinforcement Learning using Python – 8 AI Agents- Udemy
This course guides you through a step-by-step process of building state-of-the-art trading algorithms and ensures that you walk away with the practical skills to build any reinforcement learning algorithm idea you have and implement it efficiently.
Reinforcement Learning beginner to master – AI in Python- Udemy
This is the most complete Reinforcement Learning course on Udemy. In this course, you will learn the basics of Reinforcement Learning, one of the three paradigms of modern artificial intelligence. You will implement from scratch the adaptive algorithms that solve control tasks based on experience. You will also learn to combine these algorithms with Deep Learning techniques and neural networks, giving rise to the branch known as Deep Reinforcement Learning.
Deep Reinforcement Learning: Hands-on AI Tutorial in Python- Udemy
In this course you will learn the concepts and fundamentals of reinforcement learning, its relation to artificial intelligence and machine learning, and how you can formulate a problem in the context of reinforcement learning and the Markov Decision Process. It covers different fundamental algorithms including Q-Learning, SARSA as well as Deep Q-Learning. It presents the whole implementation of two projects from scratch with Q-learning and Deep Q-Network.
