【2022年】十大強化學習課程熱門排行推薦與優惠精選!

 

本文章推薦「强化学习实战系列(PyTorch版)」、「Artificial Intelligence: Reinforcement Learning in Python」、「Advanced AI: Deep Reinforcement Learning in Python」等相關強化學習線上課程,讓您滿足學習的慾望。

你是否想透過線上學習得到更多的技能,增加自己的技能樹?現在是學生的您,透過線上學習可以將更多專業知識用在課業學習上更加強所學。還是您是朝九晚五的上班族,尋找可以為工作上帶來更上一層樓的技能?或您是因為興趣或想培養其他興趣?

線上課程不受地理位置影響,不受時間早晚影響,老師來自世界各地,也不受學習程度影響的特色,讓您無時無刻想學都可以,想多看幾次增加熟悉度也可以。不同領域的老師將針對不同主題滿足您的學習目的,推薦的課程項目會陸續更新,絕對提供您最熱門人氣高的線上課程。

  • 線上課程老師來自於全球,文章推薦的熱門課程除了繁中課程以外還會有機會看到簡中和英文課程,可以針對自己喜好挑選。
  • 呈現的價錢會因為一些活動而有折扣,但折扣有可能一段時間後結束而調整回原價,最終價錢煩請到課程頁面進行確認。





強化學習課程總覽

為了節省您的時間,本列表整理每個課程精要,讓您可以快速瀏覽這文章所提供的課程是否是您所需要的,點選您有興趣課程的「課程名稱」或「課程圖示」可以進一步跳到文章所屬課程的介紹區塊瞭解更多資訊。

課程名稱Artificial Intelligence: Reinforcement Learning in PythonAdvanced AI: Deep Reinforcement Learning in PythonPractical Reinforcement Learning using Python – 8 AI AgentsCutting-Edge AI: Deep Reinforcement Learning in PythonDeep Reinforcement Learning: Hands-on AI Tutorial in PythonDeep Reinforcement Learning 2.0Reinforcement Learning with PytorchModern Reinforcement Learning: Actor-Critic AlgorithmsReinforcement Learning: AI Flight with Unity ML-Agents强化学习实战系列(PyTorch版)
課程圖示
1

Artificial Intelligence: Reinforcement Learning in Python

2

Advanced AI: Deep Reinforcement Learning in Python

3

Practical Reinforcement Learning using Python - 8 AI Agents

4

Cutting-Edge AI: Deep Reinforcement Learning in Python

5

Deep Reinforcement Learning: Hands-on AI Tutorial in Python

6

Deep Reinforcement Learning 2.0

7

Reinforcement Learning with Pytorch

8

Modern Reinforcement Learning: Actor-Critic Algorithms

9

Reinforcement Learning: AI Flight with Unity ML-Agents

10

强化学习实战系列(PyTorch版)

課程原價NT$ 2,790NT$ 2,990NT$ 2,790NT$ 2,790NT$ 2,790NT$ 2,690NT$ 1,790
課程售價NT$ 2,690NT$ 990NT$ 590NT$ 530NT$ 470NT$ 470NT$ 470NT$ 470NT$ 2,190NT$ 470
課程評價(人數)4.7 分(8,791 個評分)4.6 分(4,022 個評分)4.2 分(199 個評分)4.6 分(972 個評分)4.5 分(178 個評分)4.5 分(827 個評分)4.2 分(350 個評分)4.7 分(236 個評分)4.5 分(190 個評分)4.4 分(6 個評分)
課程時長14.5 小時10.5 小時5 小時8.5 小時4 小時9.5 小時7 小時8 小時14.5 小時10.5 小時
學生人數41,159 人33,337 人25,156 人22,547 人16,300 人7,153 人2,386 人1,413 人801 人73 人
課程特色Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising ApplicationsThe Complete Guide to Mastering Artificial Intelligence using Deep Learning and Neural NetworksUse Cutting-Edge Reinforcement Learning algorithms in Environments like Flappy Bird, Mario, Stocks and Much More!!Apply deep learning to artificial intelligence and reinforcement learning using evolution strategies, A2C, and DDPGDevelop Artificial Intelligence Applications using Reinforcement Learning in Python.The smartest combination of Deep Q-Learning, Policy Gradient, Actor Critic, and DDPGLearn to apply Reinforcement Learning and Artificial Intelligence algorithms using Python, Pytorch and OpenAI GymHow to Implement Cutting Edge Artificial Intelligence Research Papers in the Open AI Gym Using the PyTorch FrameworkTeach airplanes to fly with Unity’s Reinforcement Learning platform强化学习经典算法+案例实战
連結UdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemy



強化學習課程介紹

推薦的課程以倒序的方式呈現,越往下查看會看到越熱門的,期望您能找到滿意的學習主題!

10

强化学习实战系列(PyTorch版)

强化学习经典算法+案例实战
NT$ 1,790
NT$ 470

點擊看Udemy

課程老師唐宇迪 唐
課程評價4.4 分(6 個評分)
課程時長10.5 小時
學生人數73 人

課程介紹

强化学习系列课程主要包括经典算法原理讲解与案例实战两大部分。通俗讲解当下主流强化学习算法思想,结合实例解读算法整理应用流程并结合案例展开代码实战。整体风格通俗易懂,适合准备入门强化学习并进阶提升的同学们。课程目录界面提供全部所需PPT,数据,代码!

瞭解更多細節

哪些人適合這堂課?

  • 人工智能方向的同学们

學習目標

  • 掌握强化学习基本思想及其应用领域
  • 掌握强化学习主流算法原理
  • 掌握强化学习算法数学推导过程及其证明
  • 熟练使用PyTorch框架构建强化学习模型
  • 熟练使用Openai环境训练强化学习算法模型
  • 熟练基本强化学习算法进行实际项目构建
  • 掌握DQN,A3C等主流强化学习算法及其数学原理

關注這課程的人也購買了這些…

9

Reinforcement Learning: AI Flight with Unity ML-Agents

Teach airplanes to fly with Unity’s Reinforcement Learning platform
NT$ 2,190

點擊看Udemy

課程老師Adam Kelly Immersive Limit
課程評價4.5 分(190 個評分)
課程時長14.5 小時
學生人數801 人

課程介紹

Interested in the intersection of video games and artificial intelligence? If so, you will love Unity ML-Agents.

Reinforcement Learning with ML-Agents is naturally more intuitive than other machine learning approaches because you can watch your neur

瞭解更多細節

哪些人適合這堂課?

  • Intermediate software developers with an interest in AI in the Unity3d Game Engine
  • Developers that want to use Reinforcement Learning, but don’t need to know the low level details
  • Game developers interested in adding neural network AI to their games

學習目標

  • Learn how to install, run, and train neural networks with Unity ML-Agents
  • Train airplane agents to fly with Reinforcement Learning, specifically PPO
  • Create a full, playable airplane racing game in Unity with incredibly challenging AI opponents
  • Integrate trained neural networks in a game that can be built and deployed cross-platform
  • Utilize Machine Learning at a high level (no need to write training algorithms)
  • Lots of opportunities to customize the project and make it your own

關注這課程的人也購買了這些…



8

Modern Reinforcement Learning: Actor-Critic Algorithms

How to Implement Cutting Edge Artificial Intelligence Research Papers in the Open AI Gym Using the PyTorch Framework
NT$ 2,690
NT$ 470

點擊看Udemy

課程老師Phil Tabor
課程評價4.7 分(236 個評分)
課程時長8 小時
學生人數1,413 人

課程介紹

In this advanced course on deep reinforcement learning, you will learn how to implement policy gradient, actor critic, deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and soft actor critic (SAC) algor

瞭解更多細節

哪些人適合這堂課?

  • Advanced students of artificial intelligence who want to implement state of the art academic research papers

學習目標

  • How to code policy gradient methods in PyTorch
  • How to code Deep Deterministic Policy Gradients (DDPG) in PyTorch
  • How to code Twin Delayed Deep Deterministic Policy Gradients (TD3) in PyTorch
  • How to code actor critic algorithms in PyTorch
  • How to implement cutting edge artificial intelligence research papers in Python

關注這課程的人也購買了這些…

7

Reinforcement Learning with Pytorch

Learn to apply Reinforcement Learning and Artificial Intelligence algorithms using Python, Pytorch and OpenAI Gym
NT$ 2,790
NT$ 470

點擊看Udemy

課程老師Atamai AI Team
課程評價4.2 分(350 個評分)
課程時長7 小時
學生人數2,386 人

課程介紹

UPDATE:

All the code and installation instructions have been updated and verified to work with Pytorch 1.6 !!

Artificial Intelligence is dynamically edging its way into our lives. It is already broadly available and we use it – sometimes even no

瞭解更多細節

哪些人適合這堂課?

  • Anyone interested in artificial intelligence, data science, machine learning, deep learning and reinforcement learning.

學習目標

  • Reinforcement Learning basics
  • Tabular methods
  • Bellman equation
  • Q Learning
  • Deep Reinforcement Learning
  • Learning from video input

關注這課程的人也購買了這些…



6

Deep Reinforcement Learning 2.0

The smartest combination of Deep Q-Learning, Policy Gradient, Actor Critic, and DDPG
NT$ 2,790
NT$ 470

點擊看Udemy

課程老師Hadelin de Ponteves
課程評價4.5 分(827 個評分)
課程時長9.5 小時
學生人數7,153 人

課程介紹

Welcome to Deep Reinforcement Learning 2.0!

In this course, we will learn and implement a new incredibly smart AI model, called the Twin-Delayed DDPG, which combines state of the art techniques in Artificial Intelligence including continuous Double

瞭解更多細節

哪些人適合這堂課?

  • Data Scientists who want to take their AI Skills to the next level
  • AI experts who want to expand on the field of applications
  • Engineers who work in technology and automation
  • Businessmen and companies who want to get ahead of the game
  • Students in tech-related programs who want to pursue a career in Data Science, Machine Learning, or Artificial Intelligence
  • Anyone passionate about Artificial Intelligence

學習目標

  • Q-Learning
  • Deep Q-Learning
  • Policy Gradient
  • Actor Critic
  • Deep Deterministic Policy Gradient (DDPG)
  • Twin-Delayed DDPG (TD3)
  • The Foundation Techniques of Deep Reinforcement Learning
  • How to implement a state of the art AI model that is over performing the most challenging virtual applications

關注這課程的人也購買了這些…

5

Deep Reinforcement Learning: Hands-on AI Tutorial in Python

Develop Artificial Intelligence Applications using Reinforcement Learning in Python.
NT$ 2,790
NT$ 470

點擊看Udemy

課程老師Mehdi Mohammadi
課程評價4.5 分(178 個評分)
課程時長4 小時
學生人數16,300 人

課程介紹

In this course we learn the concepts and fundamentals of reinforcement learning, it’s relation to artificial intelligence and machine learning, and how we can formulate a problem in the context of reinforcement learning and Markov Decision Process. W

瞭解更多細節

哪些人適合這堂課?

  • Machine learning and AI enthusiasts and practitioners, data scientists, machine learning engineers.

學習目標

  • The concepts and fundamentals of reinforcement learning
  • The main algorithms including Q-Learning, SARSA as well as Deep Q-Learning.
  • How to formulate a problem in the context of reinforcement learning and MDP.
  • Apply the learned techniques to some hands-on experiments and real world projects.
  • Develop artificial intelligence applications using reinforcement learning.

關注這課程的人也購買了這些…



4

Cutting-Edge AI: Deep Reinforcement Learning in Python

Apply deep learning to artificial intelligence and reinforcement learning using evolution strategies, A2C, and DDPG
NT$ 2,990
NT$ 530

點擊看Udemy

課程老師Lazy Programmer Inc.
課程評價4.6 分(972 個評分)
課程時長8.5 小時
學生人數22,547 人

課程介紹

Welcome to Cutting-Edge AI!

This is technically Deep Learning in Python part 11 of my deep learning series, and my 3rd reinforcement learning course.

Deep Reinforcement Learning is actually the combination of 2 topics: Reinforcement Learning and

瞭解更多細節

哪些人適合這堂課?

  • Students and professionals who want to apply Reinforcement Learning to their work and projects
  • Anyone who wants to learn cutting-edge Artificial Intelligence and Reinforcement Learning algorithms

學習目標

  • Understand a cutting-edge implementation of the A2C algorithm (OpenAI Baselines)
  • Understand and implement Evolution Strategies (ES) for AI
  • Understand and implement DDPG (Deep Deterministic Policy Gradient)

關注這課程的人也購買了這些…

3

Practical Reinforcement Learning using Python – 8 AI Agents

Use Cutting-Edge Reinforcement Learning algorithms in Environments like Flappy Bird, Mario, Stocks and Much More!!
NT$ 590

點擊看Udemy

課程老師Samuel Boylan-Sajous
課程評價4.2 分(199 個評分)
課程時長5 小時
學生人數25,156 人

課程介紹

Join the most comprehensive Reinforcement Learning course on Udemy and learn how to build Amazing Reinforcement Learning Applications!

Do you want to learn how to build cutting edge trading algorithms that leverage todays technology? Or do you want

瞭解更多細節

哪些人適合這堂課?

  • Python Developers
  • Coding Enthusiast
  • People Interested in Cutting-Edge Technology

學習目標

  • Practical Reinforcement Learning
  • Master Open AI Gyms
  • Flappy Bird Agent
  • Mario Agent
  • Stocks Agents
  • Car Agents
  • Space Invaders Agent
  • and Much More!!
  • Build Reinforcement Learning Agents in Any Environment

關注這課程的人也購買了這些…



2

Advanced AI: Deep Reinforcement Learning in Python

The Complete Guide to Mastering Artificial Intelligence using Deep Learning and Neural Networks
NT$ 990

點擊看Udemy

課程老師Lazy Programmer Team
課程評價4.6 分(4,022 個評分)
課程時長10.5 小時
學生人數33,337 人

課程介紹

This course is all about the application of deep learning and neural networks to reinforcement learning.

If you’ve taken my first reinforcement learning class, then you know that reinforcement learning is on the bleeding edge of what we can do with

瞭解更多細節

哪些人適合這堂課?

  • Professionals and students with strong technical backgrounds who wish to learn state-of-the-art AI techniques

學習目標

  • Build various deep learning agents (including DQN and A3C)
  • Apply a variety of advanced reinforcement learning algorithms to any problem
  • Q-Learning with Deep Neural Networks
  • Policy Gradient Methods with Neural Networks
  • Reinforcement Learning with RBF Networks
  • Use Convolutional Neural Networks with Deep Q-Learning

關注這課程的人也購買了這些…

1

Artificial Intelligence: Reinforcement Learning in Python

Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising Applications
NT$ 2,790
NT$ 2,690

點擊看Udemy

課程老師Lazy Programmer Team
課程評價4.7 分(8,791 個評分)
課程時長14.5 小時
學生人數41,159 人

課程介紹

When people talk about artificial intelligence, they usually don’t mean supervised and unsupervised machine learning.

These tasks are pretty trivial compared to what we think of AIs doing – playing chess and Go, driving cars, and beating video games

瞭解更多細節

哪些人適合這堂課?

  • Anyone who wants to learn about artificial intelligence, data science, machine learning, and deep learning
  • Both students and professionals

學習目標

  • Apply gradient-based supervised machine learning methods to reinforcement learning
  • Understand reinforcement learning on a technical level
  • Understand the relationship between reinforcement learning and psychology
  • Implement 17 different reinforcement learning algorithms

關注這課程的人也購買了這些…



強化學習課程總覽

看完了一連串課程的介紹後,你是否還想要再一次進行課程總比較呢?

課程名稱Artificial Intelligence: Reinforcement Learning in PythonAdvanced AI: Deep Reinforcement Learning in PythonPractical Reinforcement Learning using Python – 8 AI AgentsCutting-Edge AI: Deep Reinforcement Learning in PythonDeep Reinforcement Learning: Hands-on AI Tutorial in PythonDeep Reinforcement Learning 2.0Reinforcement Learning with PytorchModern Reinforcement Learning: Actor-Critic AlgorithmsReinforcement Learning: AI Flight with Unity ML-Agents强化学习实战系列(PyTorch版)
課程圖示
1

Artificial Intelligence: Reinforcement Learning in Python

2

Advanced AI: Deep Reinforcement Learning in Python

3

Practical Reinforcement Learning using Python - 8 AI Agents

4

Cutting-Edge AI: Deep Reinforcement Learning in Python

5

Deep Reinforcement Learning: Hands-on AI Tutorial in Python

6

Deep Reinforcement Learning 2.0

7

Reinforcement Learning with Pytorch

8

Modern Reinforcement Learning: Actor-Critic Algorithms

9

Reinforcement Learning: AI Flight with Unity ML-Agents

10

强化学习实战系列(PyTorch版)

課程原價NT$ 2,790NT$ 2,990NT$ 2,790NT$ 2,790NT$ 2,790NT$ 2,690NT$ 1,790
課程售價NT$ 2,690NT$ 990NT$ 590NT$ 530NT$ 470NT$ 470NT$ 470NT$ 470NT$ 2,190NT$ 470
課程評價(人數)4.7 分(8,791 個評分)4.6 分(4,022 個評分)4.2 分(199 個評分)4.6 分(972 個評分)4.5 分(178 個評分)4.5 分(827 個評分)4.2 分(350 個評分)4.7 分(236 個評分)4.5 分(190 個評分)4.4 分(6 個評分)
課程時長14.5 小時10.5 小時5 小時8.5 小時4 小時9.5 小時7 小時8 小時14.5 小時10.5 小時
學生人數41,159 人33,337 人25,156 人22,547 人16,300 人7,153 人2,386 人1,413 人801 人73 人
課程特色Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising ApplicationsThe Complete Guide to Mastering Artificial Intelligence using Deep Learning and Neural NetworksUse Cutting-Edge Reinforcement Learning algorithms in Environments like Flappy Bird, Mario, Stocks and Much More!!Apply deep learning to artificial intelligence and reinforcement learning using evolution strategies, A2C, and DDPGDevelop Artificial Intelligence Applications using Reinforcement Learning in Python.The smartest combination of Deep Q-Learning, Policy Gradient, Actor Critic, and DDPGLearn to apply Reinforcement Learning and Artificial Intelligence algorithms using Python, Pytorch and OpenAI GymHow to Implement Cutting Edge Artificial Intelligence Research Papers in the Open AI Gym Using the PyTorch FrameworkTeach airplanes to fly with Unity’s Reinforcement Learning platform强化学习经典算法+案例实战
連結UdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemy



從老師查找更多課程

以上推薦的課程還沒挑到自己有興趣的嗎?
還是您有熱衷某個老師開的課程呢?
本頁除了提供強化學習的課程以外,也列出這些課程所屬的老師的主要資訊頁,您可以從下列選單中了解更多相關介紹或看他們開的其他課程,期望您最終能找到自己想學習的項目。



【2022年】十大強化學習課程熱門排行推薦與優惠精選!

參考其他資料科學線上課程

除了本文介紹的課程種類以外,想要瞭解資料科學領域還有哪些不同類型的課程值得一探究竟嗎?讓您可以從不同面向更紮實的學習,點擊參考以下其他熱門主題文章。絕對提供您最優惠人氣滿檔的課程,歡迎繼續延伸閱讀。


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