Artificial Intelligence and Machine Learning Courses

AI+ Game Design Agent - Self-paced

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

Course overview

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Why study this course

The AI+ Game Design Agent course is designed for game designers, developers, AI/ML engineers, and tech enthusiasts seeking to integrate artificial intelligence into modern game development. This course equips professionals with practical, industry-relevant skills to enhance game mechanics, player experience, and procedural content generation, enabling them to build smarter, more dynamic games using AI-driven techniques.

Throughout the course, learners explore key AI concepts including machine learning, reinforcement learning, pathfinding, behavior modelling, and strategic decision-making, alongside practical applications in NPC design and 3D environments. The course emphasises hands-on experience and real-world application, enabling students to design, implement, and optimise intelligent game agents while gaining the expertise needed to create adaptive, immersive gaming experiences.

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:

Learn to design, implement, and optimize AI driven game agents for interactive gameplay.
Develop proficiency in Unity3D, Playcanvas, and Pygame for AI integration in games.
Grasp AI techniques like pathfinding, reinforcement learning, and state machines for intelligent agent behavior.
Equip yourself with practical skills in developing functional AI agents for real-world gaming environments.
Tackle complex AI challenges in game design, preparing for careers in AI-driven game development.

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:

Game Designers
Game Developers
AI Enthusiasts
Aspiring Game Creators
Tech Innovators

Course subjects

Module 1: Understanding AI Agents

What are AI Agents?
Agent Architectures and Environments
Decision Making and Behavior Basics
Introduction to Multi-Agent Systems
Case Study: Pac-Man Ghost AI
Hands-On: Build a Basic Reactive AI Agent Navigating a Simple Environment Using Pygame

Module 2: Introduction to AI Game Agent

What is an AI Game Agent?
Key Components of AI Game Agent
Agent Architectures
AI Game Agent Behaviors
Case Study: Racing Games (e.g., Mario Kart, Forza Horizon)
Hands-On: Creating a Simple Box Movement Game in PlayCanvas

Module 3: Reinforcement Learning in Game Design

Basics of Reinforcement Learning
Key Algorithms: Q-Learning and SARSA
Applying RL to Game Agents
Challenges and Solutions in Game-Based RL
Case Study: AlphaZero in Games: Mastering Chess, Shogi, and Go through Self-Play and Reinforcement Learning
Hands-On: Train a Simple RL Agent in OpenAI Gym Environment

Module 4: AI for NPCs and Pathfinding

Understanding NPCs as AI Agents
Simple AI Techniques for NPCs
Pathfinding Algorithms
Obstacle Avoidance and Movement Optimization
Case Study
Hands-On

Module 5: AI for Strategic Decision-Making

Decision Trees and Minimax for Game AI
Monte Carlo Tree Search (MCTS) for AI Agents
Utility-Based Decision Making for Game AI
AI in Real-Time Strategy (RTS) Games
Case Study: StarCraft II AI by DeepMind
Hands-On: Implement a Basic MCTS Agent for Tic-Tac-Toe Using Pygame

Module 6: AI Game Agent in 3D Virtual Environments

3D Environment Representation and Challenges for AI Agents
Navigation Mesh Generation for AI Agents in 3D
Complex Agent Behaviors in 3D Worlds
Case Study: The Last of Us
Hands-On: Develop a 3D AI Agent with Navigation and Interaction in Unity Using NavMesh and C#

Module 7: Future Trends in AI Game Design

Current and Future AI Trends
The Future of Generalist AI in Gaming
Case Study

Module 8: Capstone Project

Task Description
Practical Implementation
Testing and Debugging
Hands-On

Prerequisites

Familiarity with coding concepts and languages.
Understanding of core game mechanics and structure.
Strong grasp of logic and problem-solving techniques.
Introductory knowledge of AI principles and models.
Ability to envision dynamic and interactive game elements.

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.