Deep Reinforcement Learning 20

Course Feature

Cost

Paid
Provider

Udemy
Certificate

Paid Certification
Language

English
Start Date

2023-01-09
Learners

No Information
Duration

No Information
Instructor

Hadelin de PontevesSuperDataScience TeamLigency Te

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4.4

10,246 Ratings

This Deep Reinforcement Learning 2.0 course is the perfect opportunity to learn and implement a new incredibly smart AI model. With this course, you will learn and understand the fundamentals of Artificial Intelligence, including Q-Learning, Deep Q-Learning, Policy Gradient, Actor-Critic and more. You will also gain an in-depth understanding of the Twin-Delayed DDPG model and its training process. Finally, you will be able to implement the model from scratch, step by step, and practice coding exercises on the free and open source AI platform, Google Colab. Don't miss out on this amazing opportunity to master this highly advanced model!

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Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [August 18th, 2023]

Skills and Knowledge:
By taking this course, you will acquire a wide range of skills and knowledge related to Artificial Intelligence, including Q-Learning, Deep Q-Learning, Policy Gradient, Actor-Critic, and the Twin-Delayed DDPG model. You will gain an understanding of the theory behind the model, as well as the ability to implement it from scratch using Google Colab. Additionally, you will have the opportunity to practice coding exercises and gain hands-on experience with the model.
Professional Growth:
This course contributes to professional growth by providing a comprehensive overview of the fundamentals of Artificial Intelligence, as well as a detailed explanation of the Twin-Delayed DDPG model. Through interactive coding exercises, participants will gain hands-on experience in implementing the model from scratch, and will be able to apply their knowledge to solve challenging virtual AI applications. Additionally, the course will provide participants with the opportunity to practice their skills on a free and open source AI platform, Google Colab, which will help them to stay up-to-date with the latest AI technologies.
Further Education:
This course is suitable for preparing further education as it covers the fundamentals of Artificial Intelligence, provides an in-depth look at the Twin-Delayed DDPG theory, and offers an implementation of the model from scratch. The interactive sessions and coding exercises will help to strengthen understanding of the concepts and provide hands-on experience with the model. Additionally, the use of Google Colab allows for easy access to the AI platform without the need to install any packages.

Course Syllabus

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

Special Content

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