AI+ Gaming

Hours: 8 / Access Length: 12 Months / Delivery: Online, Self-Paced
Online Hours: 8
Retail Price: $195.00

Course Overview:

This course offers a comprehensive deep dive into AI-driven game design, empowering you to master intelligent NPC development and adaptive storytelling through hands-on, real-world projects. By earning this industry-recognized certificate, you will gain future-ready expertise in generative AI and predictive analytics, unlocking advanced career opportunities across the gaming and virtual production industries.

Recommended Prerequisites:

• Basic Programming Skills – Comfortable with Python or similar languages.
• Foundational Math Knowledge – Understanding of linear algebra and probability.
• Intro to Machine Learning – Familiarity with ML concepts and algorithms.
• Game Development Exposure – Experience with Unity or Unreal Engine basics.
• Problem-Solving Mindset – Ability to approach challenges creatively and logically.

Course Outline:

Lesson 1: Introduction to AI in Games

• 1.1 What is AI?
• 1.2 Evolution of AI in the Gaming Industry
• 1.3 Types of AI in Games
• 1.4 Benefits, Challenges, and Innovations in Game AI

Lesson 2: Game Design Principles using AI

• 2.1 Understanding Game Mechanics and Player Experience
• 2.2 Role of AI in Gameplay and Narrative Design
• 2.3 Designing Game Environments for AI Interaction
• 2.4 AI-Driven Behavior vs Traditional Scripted Logic
• 2.5 Case Study: Dynamic AI and Narrative Adaptation in Middle earth: Shadow of Mordor
• 2.6 Hands-On Exercise: Designing Adaptive NPC Behavior and Environment Interaction

Lesson 3: Foundations of AI in Gaming

• 3.1 Core AI Concepts for Gaming
• 3.2 Search Algorithms and Pathfinding
• 3.3 AI Behavior Modeling and Procedural Content Generation (PCG)
• 3.4 Introduction to Machine Learning and Reinforcement Learning
• 3.5 Case Study: AI in Minecraft — Procedural Content Generation and Agent Navigation
• 3.6 Hands-On: Implementing A* Pathfinding and FSM for NPC Behavior

Lesson 4: Reinforcement Learning Fundamentals

• 4.1 Core Concepts: States, Actions, Rewards, Policies, Q-Learning:
• 4.2 Exploration versus Exploitation in Learning Systems:
• 4.3 Overview of Deep Q Networks (DQN) and Policy Gradient Methods
• 4.4 Case Study: Reinforcement Learning in DeepMind’s AlphaGo
• 4.5 Hands-On: Train a Reinforcement Learning Model on OpenAI Gym’s GridWorld

Lesson 5: Planning and Decision Making in Games

• 5.1 Minimax Algorithm and Alpha-Beta Pruning
• 5.2 Monte Carlo Tree Search (MCTS)
• 5.3 Applications in Board Games and Real-Time Strategy (RTS) Games
• 5.4 Case Study: Strategic AI in StarCraft II – Combining Planning Algorithms for Real-Time Strategy
• 5.5 Hands-on Implementation: Guides on implementing the Minimax algorithm for Tic-Tac-Toe

Lesson 6: AI Techniques in 2D/3D Virtual Gaming Environments Basic

• 6.1 Overview of 2D and 3D Game Environments
• 6.2 Environment Representation Techniques
• 6.3 Navigation and Pathfinding in 2D/3D Spaces
• 6.4 Interaction and Behavior Systems in Virtual Environments
• 6.5 Case Study: Navigation and Interaction AI in The Legend of Zelda: Breath of the Wild
• 6.6 Hands-On: Building Basic Navigation and Interaction in 2D and 3D Game Environments

Lesson 7: Adaptive Systems and Dynamic Difficulty

• 7.1 Adaptive Systems Overview
• 7.2 Dynamic Difficulty Adjustment (DDA) Principles
• 7.3 Adaptive Storytelling, Personalization, and Player Profiling
• 7.4 AI Techniques in Adaptive Systems
• 7.5 Implementation Strategies and Tools
• 7.6 Case Study: Dynamic Enemy Management and Replayability with Left 4 Dead’s AI Director
• 7.7 Hands-On: Developing an Adaptive Dynamic Difficulty System in Unity

Lesson 8: Future of AI in Gaming

• 8.1 Generalist AI Agents and Transfer Learning
• 8.2 AI-Powered Game Design and Testing Tools
• 8.3 Ethical Considerations and AI Transparency
• 8.4 Emerging Technologies: VR/AR AI and AI in Esports Coaching

Lesson 9: Capstone Project

All necessary course materials are included.

System Requirements:

Internet Connectivity Requirements:

• Cable, Fiber, DSL, or LEO Satellite (i.e. Starlink) internet with speeds of at least 10mb/sec download and 5mb/sec upload are recommended for the best experience.

NOTE: While cellular hotspots may allow access to our courses, users may experience connectivity issues by trying to access our learning management system.  This is due to the potential high download and upload latency of cellular connections.   Therefore, it is not recommended that students use a cellular hotspot as their primary way of accessing their courses.

Hardware Requirements:

• CPU: 1 GHz or higher
• RAM: 4 GB or higher
• Resolution: 1280 x 720 or higher.  1920x1080 resolution is recommended for the best experience.
• Speakers / Headphones
• Microphone for Webinar or Live Online sessions.

Operating System Requirements:

• Windows 7 or higher.
• Mac OSX 10 or higher.
• Latest Chrome OS
• Latest Linux Distributions
  

NOTE: While we understand that our courses can be viewed on Android and iPhone devices, we do not recommend the use of these devices for our courses. The size of these devices do not provide a good learning environment for students taking online or live online based courses.

Web Browser Requirements:

• Latest Google Chrome is recommended for the best experience.
• Latest Mozilla FireFox
• Latest Microsoft Edge
• Latest Apple Safari

Basic Software Requirements (These are recommendations of software to use):

• Office suite software (Microsoft Office, OpenOffice, or LibreOffice)
• PDF reader program (Adobe Reader, FoxIt)
• Courses may require other software that is described in the above course outline.