The Beginner Guide to Artificial Intelligence (Unity 2022)

The Beginners Guide to Artificial Intelligence (Unity 2022), available at $99.99, has an average rating of 4.64, with 185 lectures, 1 quizzes, based on 2617 reviews, and has 42536 subscribers.

You will learn about Design and program NPCs with C# in Unity Explain how AI is applied in computer games Implement AI-related Unity Asset plugins into existing projects Work with a variety of AI techniques for developing navigation and decision making abilities in NPCs This course is ideal for individuals who are Anyone interested in learning how to program their own non-player characters (NPCs). or Anyone interested in seeing how artificial intelligence is applied in computer games. It is particularly useful for Anyone interested in learning how to program their own non-player characters (NPCs). or Anyone interested in seeing how artificial intelligence is applied in computer games.

Enroll now: The Beginners Guide to Artificial Intelligence (Unity 2022)

Summary

Title: The Beginners Guide to Artificial Intelligence (Unity 2022)

Price: $99.99

Average Rating: 4.64

Number of Lectures: 185

Number of Quizzes: 1

Number of Published Lectures: 185

Number of Published Quizzes: 1

Number of Curriculum Items: 186

Number of Published Curriculum Objects: 186

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Design and program NPCs with C# in Unity

Explain how AI is applied in computer games

Implement AI-related Unity Asset plugins into existing projects

Work with a variety of AI techniques for developing navigation and decision making abilities in NPCs

Who Should Attend

Anyone interested in learning how to program their own non-player characters (NPCs).

Anyone interested in seeing how artificial intelligence is applied in computer games.

Target Audiences

Anyone interested in learning how to program their own non-player characters (NPCs).

Anyone interested in seeing how artificial intelligence is applied in computer games.

Do your non-player characters (NPCs) lack drive and ambition?  Are they slow, stupid and constantly banging their heads against the wall? Then this course is for you.  Join Penny as she explains, demonstrates and assists you in creating your very own NPCs in Unity with C#. All you need is a sound knowledge of Unity, C# and the ability to add two numbers together.

This course uses Unity Version 2021.3 LTS

In this course, Penny reveals the most popular AI techniques used for creating believable character behaviour in games using her internationally acclaimed teaching style and knowledge from over 30 years working with games, graphics and having written two award winning books on games AI. Throughout, you will follow along with hands-on workshops designed to teach you about the fundamental AI techniques used in today’s games.  You’ll join in as NPCs are programmed to chase, patrol, shoot, race, crowd and much more.

Learn how to program and work with:

vectors

waypoints

navmeshes

the A* algorithm

crowds

flocks

animated characters

vehicles

and industry standard techniques such as goal-oriented action learning and behaviour trees.

Contents and Overview

The course begins with a detailed examination of vector mathematics that sits at the very heart of programming the movement of NPCs. Following this, systems of waypoints will be used to move characters around in an environment before examining the Unity waypoint system for car racing with AI controlled cars.  This leads into an investigation of graph theory and the A* algorithm before we apply these principles to developing navmeshes and developing NPCs who can find their way around a game environment.  Before an aquarium is programmed complete with autonomous schooling fish, crowds of people will be examined from the recreation of sidewalk traffic, to groups of people fleeing from danger. Having examined the differing ways to move NPCs around in a game environment, their thinking abilities will be discussed with full explanations and more hands-on workshops using finite state machines and behaviour trees.

The follow-along workshops included in the course come with starter Unity asset files and projects complete with solutions.  Throughout, there are also quizzes and challenge exercises to reinforce your learning and guide you to express your newfound knowledge.

At the completion of this course you will have gained a broad understanding of what AI is in games, how it works and how you can use it in your own projects.  It will equip you with a toolset to examine any of the techniques presented in more depth to take your game environments to the next level.

What students are saying about this course:

This has been my favourite Udemy-Unity course so far. It took me from literally 0% knowledge of how game AI is achieved, and took me to a whole new level. Waypoints, pathfinding, state machines, etc etc etc are all covered in-depth and will reveal the magic (spoiler alert: it isn’t magic) behind making your computer characters seem like they really have a mind of their own.

Oh My God. I love her way of teaching things. I haven’t finished this course yet. But all i can say is that it is another brilliant course from her. Artificial intelligence by itself is a tricky thing to do. And before starting this course i never thought that i will understand anything in it. But i was wrong. With her style of teaching, you will learn how to move your characters in an ”intelligent“ way. This course is perfectly sliced and the pace is wonderful.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Welcome to the Course

Lecture 2: Introduction to Artificial Intelligence

Lecture 3: Join the H3D Student Community

Lecture 4: FAQs

Lecture 5: Not So Scary Vector Mathematics

Lecture 6: Vector Mathematics Basics Cheat Sheet

Chapter 2: The Mathematics of AI

Lecture 1: The Cartesian plane

Lecture 2: Vectors Part 1

Lecture 3: Vectors Part 2

Lecture 4: Vectors Part 3

Lecture 5: Calculating Distance Part 1

Lecture 6: Calculating Distance Part 2

Lecture 7: Calculating the Dot Product

Lecture 8: Calculating the Angle Between Vectors

Lecture 9: Calculating the Cross Project

Lecture 10: A Simple Autopilot Project

Lecture 11: A Simple AI Pet Challenge Project

Chapter 3: The Physics of AI

Lecture 1: Time

Lecture 2: Normalising Movement with Time

Lecture 3: Velocity

Lecture 4: Predicting Future Locations of Game Objects Part 1

Lecture 5: Predicting Future Locations of Game Objects Part 2

Lecture 6: Acceleration Part 1

Lecture 7: Acceleration Part 2

Lecture 8: Acceleration Part 3

Lecture 9: Trajectories Part 1

Lecture 10: Trajectories Part 2

Lecture 11: Trajectories Part 3

Chapter 4: The A* Algorithm

Lecture 1: The A* Pathfinding Algorithm Part 1

Lecture 2: The A* Pathfinding Algorithm Part 2

Lecture 3: The A* Pathfinding Algorithm Part 3

Lecture 4: The A* Pathfinding Algorithm Part 4

Lecture 5: The A* Pathfinding Algorithm Part 5

Lecture 6: The A* Pathfinding Algorithm Part 6

Chapter 5: Waypoints and Graphs

Lecture 1: Waypoints

Lecture 2: Slerping to the Direction of Travel

Lecture 3: Following a Circuit

Lecture 4: Following a Tracker

Lecture 5: Using A* with Waypoints Part 1

Lecture 6: A Simple Graph API Part 1

Lecture 7: A Simple Graph API Part 2

Lecture 8: A Simple Graph API Part 3

Lecture 9: Using A* with Waypoints Part 2

Lecture 10: Traversing a Path

Lecture 11: Giving Commands to Pathfind

Chapter 6: Vehicles

Lecture 1: Setting up Wheel Physics

Lecture 2: Forces on Wheels

Lecture 3: Constructing a Simple Car

Lecture 4: Turning the Steering Wheel

Lecture 5: Creating A Circuit with Waypoints

Lecture 6: Automatically Driving a Circuit Part 1

Lecture 7: Braking

Lecture 8: Driving Forces

Lecture 9: Improved Driving Tactics

Lecture 10: Adding a Progress Tracker

Lecture 11: Adding Antiroll Stabilising

Lecture 12: Reconfiguring for Car Setting Testing

Lecture 13: Avoiding Other Drivers

Lecture 14: Improving Avoidance and Reversing

Chapter 7: Navigation Meshes

Lecture 1: Navigation Mesh Introduction

Lecture 2: From Waypoints to Navigation Meshes

Lecture 3: NavMesh Agents Part 1

Lecture 4: NavMesh Agents Part 2

Lecture 5: NavMesh Agents Part 3

Lecture 6: Following a Player on a NavMesh

Chapter 8: Finite State Machines

Lecture 1: Finite State Machines

Lecture 2: Creating a State Class

Lecture 3: Patrolling

Lecture 4: Building the AI Class

Lecture 5: Chasing the Player Part 1

Lecture 6: Chasing the Player Part 2

Lecture 7: FSM Challenge

Chapter 9: Autonomously Moving Agents

Lecture 1: Seek and Flee

Lecture 2: Pursuit

Lecture 3: Evade

Lecture 4: Wander

Lecture 5: Hide Part 1

Lecture 6: Hide Part 2

Lecture 7: Hide Part 3

Lecture 8: Complex Behaviours

Lecture 9: Behaviour Challenge

Chapter 10: Crowd Simulation

Lecture 1: Moving As One

Lecture 2: Creating a City Crowd Part 1

Lecture 3: Creating a City Crowd Part 2

Lecture 4: Fleeing Part 1

Lecture 5: Fleeing Part 2

Lecture 6: Flocking Part 1

Lecture 7: Flocking Part 2

Lecture 8: Flocking Part 3

Instructors

Penny de Byl
International Award Winning Professor & Best Selling Author

Penny Holistic3D
Academic, Author & Game Development Enthusiast

Rating Distribution

1 stars: 24 votes

2 stars: 31 votes

3 stars: 156 votes

4 stars: 722 votes

5 stars: 1684 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!