10最好的强化学习教程推荐

"This post includes affiliate links for which I may make a small commission at no extra cost to you should you make a purchase."

特写 iPhone，显示 Udemy 应用程序和带笔记本的笔记本电脑有数以千计的在线课程和课程可以帮助您提高 强化学习 技能并获得 强化学习 证书。

在这篇博客文章中，我们的专家汇总了 10 个精选列表 最好的 强化学习 课程, 现在在线提供的教程、培训计划、课程和认证。

我们只包括那些符合我们高质量标准的课程。我们花了很多时间和精力来为您收集这些。这些课程适合所有级别的初学者、中级学习者和专家。

以下是这些课程以及它们为您提供的内容！

10最好的强化学习教程推荐

课程名 在校生（人数） 评论（计数）
1. Artificial Intelligence: Reinforcement Learning in Python 我们的最佳选择 42522+ 9198+
2. Advanced AI: Deep Reinforcement Learning in Python 35250+ 4567+
3. Cutting-Edge AI: Deep Reinforcement Learning in Python 25646+ 1475+
4. Practical Reinforcement Learning using Python – 8 AI Agents 25403+ 240+
5. Deep Reinforcement Learning: Hands-on AI Tutorial in Python 16382+ 202+
6. Deep Reinforcement Learning 2.0 8582+ 1004+
7. Reinforcement Learning with Pytorch 2514+ 379+
8. Modern Reinforcement Learning: Actor-Critic Algorithms 2284+ 352+
9. Reinforcement Learning beginner to master – AI in Python 2155+ 267+
10. Reinforcement Learning: AI Flight with Unity ML-Agents 892+ 211+

1. Artificial Intelligence: Reinforcement Learning in Python 经过 “Lazy Programmer Team, Lazy Programmer Inc.” Udemy课程 我们的最佳选择

“Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising Applications”

截至目前，超过 42522+ 人们已经注册了这门课程，而且已经结束了 9198+ 评论.

课程内容
Welcome
Return of the Multi-Armed Bandit
High Level Overview of Reinforcement Learning
Markov Decision Proccesses
Dynamic Programming
Monte Carlo
Temporal Difference Learning
Approximation Methods
Interlude: Common Beginner Questions
Stock Trading Project with Reinforcement Learning
Setting Up Your Environment (FAQ by Student Request)
Extra Help With Python Coding for Beginners (FAQ by Student Request)
Effective Learning Strategies for Machine Learning (FAQ by Student Request)
Appendix / FAQ Finale

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

2. Advanced AI: Deep Reinforcement Learning in Python 经过 “Lazy Programmer Team, Lazy Programmer Inc.” Udemy课程

The Complete Guide to Mastering Artificial Intelligence using Deep Learning and Neural Networks

截至目前，超过 35250+ 人们已经注册了这门课程，而且已经结束了 4567+ 评论.

课程内容
Introduction and Logistics
The Basics of Reinforcement Learning
OpenAI Gym and Basic Reinforcement Learning Techniques
TD Lambda
Policy Gradients
Deep Q-Learning
A3C
Theano and Tensorflow Basics Review
Setting Up Your Environment (FAQ by Student Request)
Extra Help With Python Coding for Beginners (FAQ by Student Request)
Effective Learning Strategies for Machine Learning (FAQ by Student Request)
Appendix / FAQ Finale

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

3. Cutting-Edge AI: Deep Reinforcement Learning in Python 经过 Lazy Programmer Inc. Udemy课程

“Apply deep learning to artificial intelligence and reinforcement learning using evolution strategies, A2C, and DDPG”

截至目前，超过 25646+ 人们已经注册了这门课程，而且已经结束了 1475+ 评论.

课程内容
Welcome
Review of Fundamental Reinforcement Learning Concepts
A2C (Advantage Actor-Critic)
DDPG (Deep Deterministic Policy Gradient)
ES (Evolution Strategies)
Setting Up Your Environment (FAQ by Student Request)
Extra Help With Python Coding for Beginners (FAQ by Student Request)
Effective Learning Strategies for Machine Learning (FAQ by Student Request)
Appendix / FAQ Finale

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

4. Practical Reinforcement Learning using Python – 8 AI Agents 经过 The A.I. Whisperer Udemy课程

“Use Cutting-Edge Reinforcement Learning algorithms in Environments like Flappy Bird, Mario, Stocks and Much More!!”

截至目前，超过 25403+ 人们已经注册了这门课程，而且已经结束了 240+ 评论.

课程内容
Introduction
SpaceInvaders Agent
Autonomous Taxi Agent
Flappy Bird Reinforcement Learning Agent
Mario Reinforcement Learning Agent
Stocks Reinforcement Learning Agents
Car Reinforcement Learning Agents
Code for Course

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

5. Deep Reinforcement Learning: Hands-on AI Tutorial in Python 经过 Mehdi Mohammadi Udemy课程

Develop Artificial Intelligence Applications using Reinforcement Learning in Python.

截至目前，超过 16382+ 人们已经注册了这门课程，而且已经结束了 202+ 评论.

课程内容
Introduction
Jump into Reinforcement Learning
RL Algorithms
Hands-on Project 1 – Maze Problem
Hands-on Project 2 – Stock Trading
Summary

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

6. Deep Reinforcement Learning 2.0 经过 “Hadelin de Ponteves, Ligency I Team, Ligency Team” Udemy课程

“The smartest combination of Deep Q-Learning, Policy Gradient, Actor Critic, and DDPG”

截至目前，超过 8582+ 人们已经注册了这门课程，而且已经结束了 1004+ 评论.

课程内容
Part 1 – Fundamentals
Part 2 – Twin Delayed DDPG Theory
Part 3 – Twin Delayed DDPG Implementation
The Final Demo!
Annex 1 – Artificial Neural Networks
Annex 2 – Q-Learning
Annex 3 – Deep Q-Learning
Bonus Lectures

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

7. Reinforcement Learning with Pytorch 经过 Atamai AI Team Udemy课程

“Learn to apply Reinforcement Learning and Artificial Intelligence algorithms using Python, Pytorch and OpenAI Gym”

截至目前，超过 2514+ 人们已经注册了这门课程，而且已经结束了 379+ 评论.

课程内容
Welcome to the course
Introduction
Tabular methods
Scaling up
DQN
DQN Improvements
DQN with video output
Final notes

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

8. Modern Reinforcement Learning: Actor-Critic Algorithms 经过 Phil Tabor Udemy课程

How to Implement Cutting Edge Artificial Intelligence Research Papers in the Open AI Gym Using the PyTorch Framework

截至目前，超过 2284+ 人们已经注册了这门课程，而且已经结束了 352+ 评论.

课程内容
Introduction
Fundamentals of Reinforcement Learning
Landing on the Moon with Policy Gradients & Actor Critic Methods
Deep Deterministic Policy Gradients (DDPG): Actor Critic with Continuous Actions
Twin Delayed Deep Deterministic Policy Gradients (TD3)
Soft Actor Critic

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

9. Reinforcement Learning beginner to master – AI in Python 经过 Escape Velocity Labs Udemy课程

“Build Artificial Intelligence (AI) agents using Deep Reinforcement Learning and PyTorch: A2C, REINFORCE, DQN, etc.”

截至目前，超过 2155+ 人们已经注册了这门课程，而且已经结束了 267+ 评论.

课程内容
Welcome module
The Markov decision process (MDP)
Dynamic Programming
Monte Carlo methods
Temporal difference methods
N-step bootstrapping
Continuous state spaces
Brief introduction to neural networks
Deep SARSA
Deep Q-Learning
REINFORCE
Advantage Actor-Critic (A2C)
Outro

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

10. Reinforcement Learning: AI Flight with Unity ML-Agents 经过 Adam Kelly Immersive Limit Udemy课程

Teach airplanes to fly with Unity’s Reinforcement Learning platform

截至目前，超过 892+ 人们已经注册了这门课程，而且已经结束了 211+ 评论.

课程内容
COURSE UPDATES
[v0.11] Unity ML-Agents – Introduction & Setup
[v1.0] Unity ML-Agents – Introduction & Setup
[v1.0 & v0.11] Asset Creation in Blender
[v0.11] Project Setup & ML-Agents Installation
[v1.0] Project Setup & ML-Agents Installation
[v1.0 & v0.11] Desert Race Path Creation
[v0.11] Aircraft Area
[v1.0] Aircraft Area
[v0.11] Aircraft Agent & Aircraft Player
[v1.0] Aircraft Agent & Aircraft Player
[v0.11] Training the Aircraft Agents
[v1.0] Training the Aircraft Agents
[v1.0 & v0.11] Game Logic & Menus

单击此处获得 95% OFF 折扣，当您单击时将自动应用折扣

下面是一些关于学习的常见问题强化学习

学习强化学习需要多长时间？

“学习强化学习需要多长时间”这个问题的答案是。 . .这取决于。每个人都有不同的需求，每个人都在不同的场景下工作，所以一个人的答案可能与另一个人的答案完全不同。

考虑这些问题：你想学习 强化学习 是为了什么？你的出发点在哪里？您是初学者还是有使用 强化学习 的经验？你能练习多少？每天1小时？每周40小时？ 查看本课程关于 强化学习.

强化学习 学起来容易还是难？

不，学习 强化学习 对大多数人来说并不难。检查这个 关于如何学习的课程 强化学习 立刻！

如何快速学习强化学习？

学习 强化学习 最快的方法是先得到这个 强化学习 课程, 然后尽可能练习你学到的任何东西。即使每天只有 15 分钟的练习。一致性是关键.

在哪里学习 强化学习？

如果您想探索和学习 强化学习，那么 Udemy 为您提供了学习 强化学习 的最佳平台。查看此 关于如何学习的课程 强化学习 立刻！