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A Beginner’s Guide To Machine Learning with Unity

Advanced games AI with genetic algorithms, neural networks & Q-learning in C# and Tensorflow for Unity
4.6
4.6/5
(1,683 reviews)
20,382 students
Created by

9.6

CourseMarks Score®

10.0

Freshness

8.5

Feedback

9.8

Content

Platform: Udemy
Video: 13h 4m
Language: English
Next start: On Demand

Top Machine Learning courses:

Detailed Analysis

CourseMarks Score®

9.6 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

10.0 / 10
This course was last updated on 8/2021 .

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.5 / 10
We analyzed factors such as the rating (4.6/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

9.8 / 10
Video Score: 9.6 / 10
The course includes 13h 4m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 6 hours 15 minutes of 454 Machine Learning courses on Udemy.
Detail Score: 10.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.9 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

23 articles.
44 resources.
0 exercise.
0 test.

Table of contents

Description

What if you could build a character that could learn while it played?  Think about the types of gameplay you could develop where the enemies started to outsmart the player. This is what machine learning in games is all about. In this course, we will discover the fascinating world of artificial intelligence beyond the simple stuff and examine the increasingly popular domain of machines that learn to think for themselves.
In this course, Penny introduces the popular machine learning techniques of genetic algorithms and neural networks using her internationally acclaimed teaching style and knowledge from a Ph.D in game character AI and over 25 years experience working with games and computer graphics.  In addition she’s written two award winning books on games AI and two others best sellers on Unity game development. Throughout the course you will follow along with hands-on workshops designed to teach you about the fundamental machine learning techniques, distilling the mathematics in a way that the topic becomes accessible to the most noob of novices.  
Learn how to program and work with:
•genetic algorithms
•neural networks
•human player captured training sets
•reinforcement learning
•Unity’s ML-Agent plugin
•Tensorflow
Contents and Overview
The course starts with a thorough examination of genetic algorithms that will ease you into one of the simplest machine learning techniques that is capable of extraordinary learning. You’ll develop an agent that learns to camouflage, a Flappy Bird inspired application in which the birds learn to make it through a maze and environment-sensing bots that learn to stay on a platform.
Following this, you’ll dive right into creating your very own neural network in C# from scratch.  With this basic neural network, you will find out how to train behaviour, capture and use human player data to train an agent and teach a bot to drive.  In the same section you’ll have the Q-learning algorithm explained, before integrating it into your own applications.
By this stage, you’ll feel confident with the terminology and techniques used throughout the deep learning community and be ready to tackle Unity’s experimental ML-Agents. Together with Tensorflow, you’ll be throwing agents in the deep-end and reinforcing their knowledge to stay alive in a variety of game environment scenarios.
By the end of the course, you’ll have a well-equipped toolset of basic and solid machine learning algorithms and applications, that will see you able to decipher the latest research publications and integrate the latest developments into your work, while keeping abreast of Unity’s ML-Agents as they evolve from experimental to production release.
What students are saying about this course:
•Absolutely the best beginner to Advanced course for Neural Networks/ Machine Learning if you are a game developer that uses C# and Unity. BAR NONE x Infinity.
•A perfect course with great math examples and demonstration of the TensorFlow power inside Unity. After this course, you will get the strong basic background in the Machine Learning.
•The instructor is very engaging and knowledgeable. I started learning from the first lesson and it never stopped. If you are interested in Machine Learning , take this course.

You will learn

✓ Build a genetic algorithm from scratch in C#.
✓ Build a neural network from scratch in C#.
✓ Setup and explore the Unity ML-Agents plugin.
✓ Setup and use Tensorflow to train game characters.
✓ Apply newfound knowledge of machine learning to integrate contemporary research ideas in the field into their own projects.
✓ Distill the mathematics and statistic behind machine learning to working program code.
✓ Use a Proximal Policy Optimisation to train a neural network.

Requirements

• You should be familiar with the Unity Game Engine.
• You should have a working knowledge of C#.
• You should have a healthy appreciation for mathematics and statistics.

This course is for

• Anyone wanting to learn about the potential of machine learning in games.
• Anyone wanting a deeper understanding of the algorithms and theories underlying Unity’s ML-Agents.
• Anyone wanting to know how to setup and work with ML-Agents.

How much does the A Beginner's Guide To Machine Learning with Unity course cost? Is it worth it?

The course costs $15.99. And currently there is a 20% discount on the original price of the course, which was $19.99. So you save $4 if you enroll the course now.
The average price is $17.2 of 454 Machine Learning courses on Udemy.

Does the A Beginner's Guide To Machine Learning with Unity course have a money back guarantee or refund policy?

YES, A Beginner’s Guide To Machine Learning with Unity has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the A Beginner's Guide To Machine Learning with Unity course, but there is a $4 discount from the original price ($19.99). So the current price is just $15.99.

Who is the instructor? Is Penny de Byl a SCAM or a TRUSTED instructor?

Penny de Byl has created 26 courses that got 18,885 reviews which are generally positive. Penny de Byl has taught 121,111 students and received a 4.6 average review out of 18,885 reviews. Depending on the information available, Penny de Byl is a TRUSTED instructor.
International Award Winning Professor & Best Selling Author
Hi, I’m Dr Penny de Byl.  I’m a full stack developer of most things computer sciency and academic with a true passion for teaching.  I’ve been teaching others about games development, programming, computer graphics, animation and web design for over 25 years in universities in Australia and Europe at the full professor level. I’ve also consulted for Unity, SAE, the Australian Institute of Entertainment and Wikitude. My best selling textbooks including Holistic Game Development with Unity are used in over 100 institutions world-wide.  My graduates work at companies like Apple, Ubisoft, LinkedIn and Deloitte Digital.

I have an honours degree in computer graphics and a Ph.D. in artificial intelligence for games characters.  Over the course of my career I’ve won numerous awards for teaching excellence at the state, national and international levels including the Australian Learning and Teaching Council’s Excellence in Teaching Award and the Unity Mobile Game Curriculum Competition. My approach to teaching computer science and related fields is project-based giving you hands-on workshops you can immediately get your teeth into.

I want you to leave my virtual classroom fully armed with a toolkit of skills for life-long learning.  I’m excited to now be focussing my efforts full-time on Udemy to bring my years of knowledge and experience to those eager to learn about technology.


9.6

CourseMarks Score®

10.0

Freshness

8.5

Feedback

9.8

Content

Platform: Udemy
Video: 13h 4m
Language: English
Next start: On Demand

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