Artificial Intelligence and Machine Learning Courses

AI+ Gaming - Self-paced

Length 365 days access
Price NZD 500 exc GST
Inclusions Online exam

Course overview

Book your on demand course

Why study this course

The AI+ Gaming course is designed for game designers, developers, AI/ML engineers, data scientists, and tech enthusiasts looking to integrate AI into next-generation game development. The course delivers practical, industry-aligned skills in AI-driven game design, equipping professionals in these roles to enhance game mechanics, player experience, and procedural content generation while preparing for certification assessment.

Throughout the course, learners will explore essential topics such as machine learning, neural networks, pathfinding, behaviour modelling, and reinforcement learning, alongside their application in NPC design and strategic decision-making. Emphasising hands-on, real-world experience, the course enables students to design and implement intelligent game agents, giving them the expertise to build adaptive, immersive, and dynamic gaming environments.

Exam and certification

This course prepares students for the corresponding certification. The exam/assessment is completed online and provided as part of the course content.

The exam is:

90 minutes
50 multiple choice / multiple response questions
Pass mark is 35 out of 50 (i.e. 70%)
Online via AI Proctoring platform

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What you’ll learn

Through this course, students will be able to:

Gain a solid grasp of how AI transforms modern game development and enhances gameplay.
Explore intelligent NPC design, procedural content generation, and adaptive game mechanics for immersive experiences.
Acquire hands-on experience using AI tools to create responsive and dynamic gaming environments.
Learn to use AI to personalize gameplay, adjust difficulty levels, and craft dynamic storytelling.
Understand ethical considerations, fairness in game AI, and the responsible use of player data.

AI CERTs at Lumify Work

AI CERTs® stands at the forefront of AI and blockchain certification, offering world-class programs that prepare individuals to lead in these rapidly growing fields. AI CERTs courses and certifications are vendor agnostic and designed to bridge the gap between theoretical knowledge and practical application, ensuring learners are equipped to make an immediate impact in their careers.
Lumify Work is a Platinum Authorized Training Partner for AI CERTs in Australia, New Zealand, and the Philippines.

View all AI CERTs at Lumify Work courses

Who is the course for?

This course is intended for:

Aspiring Game Developers
AI Enthusiasts
Game Designers
Tech-Savvy Professionals
Students and Graduates

Course subjects

Module 1: Introduction to AI in Games

What is AI?
Evolution of AI in the Gaming Industry
Types of AI in Games
Benefits, Challenges, and Innovations in Game AI

Module 2: Game Design Principles using AI

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

Module 3: Foundations of AI in Gaming

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

Module 4: Reinforcement Learning Fundamentals

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

Module 5: Planning and Decision Making in Games

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

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

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

Module 7: Adaptive Systems and Dynamic Difficulty

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

Module 8: Future of AI in Gaming

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

Module 9: Capstone Project

Prerequisites

Comfortable with Python or similar languages.
Understanding of linear algebra and probability.
Familiarity with ML concepts and algorithms.
Experience with Unity or Unreal Engine basics.
Ability to approach challenges creatively and logically.

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.