Empower creators with AI + Game Design Agent™ to craft intelligent, dynamic, and immersive gaming experiences.
Description
About This Course
Comprehensive Skill Development
Master AI-driven game design by integrating procedural generation, adaptive storytelling, and intelligent NPC behavior to create immersive, dynamic gaming experiences.
Industry Recognition
Earn a globally recognized certification that highlights your expertise in blending artificial intelligence with creative game development.
Hands-On Learning
Practice with real-world projects involving AI-based level design, character behavior modeling, and player experience optimization to sharpen your practical game design skills.
Career Advancement
Explore opportunities in AI game development, interactive design, and simulation engineering across gaming studios, tech companies, and entertainment platforms.
Future-Ready Expertise
Stay ahead in the next era of gaming innovation with deep knowledge of generative AI, autonomous systems, and adaptive gameplay design.
Course Modules
1
Module 1: Understanding AI Agents
1.1 What are AI Agents?
1.2 Agent Architectures and Environments
1.3 Decision Making and Behavior Basics
1.4 Introduction to Multi-Agent Systems
1.5 Case Study: Pac-Man Ghost AI
1.6 Hands On: Build a Basic Reactive AI Agent Navigating a Simple Environment Using Pygame
2
Module 2: Introduction to AI Game Agent
2.1 What is an AI Game Agent?
2.2 Key Components of AI Game Agent
2.3 Agent Architectures
2.4 AI Game Agent Behaviors
2.5 Case Study: Racing Games (e.g., Mario Kart, Forza Horizon)
2.6 Hands-On: Creating a Simple Box Movement Game in Playcanvas
3
Module 3: Reinforcement Learning in Game Design
3.1 Basics of Reinforcement Learning
3.2 Key Algorithms: Q-Learning and SARSA
3.3 Applying RL to Game Agents
3.4 Challenges and Solutions in Game-based RL
3.5 Case Study: AlphaZero in Games: Mastering Chess, Shogi, and Go through Self-Play and Reinforcement Learning
3.6 Hands On: Train a simple RL agent in OpenAI Gym environment
4
Module 4: AI for NPCs and Pathfinding
4.1 Understanding NPCs as AI Agents
4.2 Simple AI Techniques for NPCs
4.3 Pathfinding Algorithms
4.4 Obstacle Avoidance and Movement Optimization
4.5 Case Study
4.6 Hands-On
5
Module 5: AI for Strategic Decision-Making
5.1 Decision Trees and Minimax for Game AI
5.2 Monte Carlo Tree Search (MCTS) for AI Agent
5.3 Utility-Based Decision Making for Game AI
5.4 AI in Real-Time Strategy (RTS) Games
5.5 Case Study: StarCraft II AI by DeepMind
5.6 Hands-On: Implement a Basic MCTS Agent for Tic-Tac-Toe Using Pygame
6
Module 6: AI Game Agent in 3D Virtual Environments
6.1 3D Environment Representation and Challenges for AI Agents
6.2 Navigation Mesh Generation for AI Agents in 3D
6.3 Complex Agent Behaviors in 3D Worlds
6.4 Case Study: The Last of Us
6.5 Hands On: Develop a 3D AI Agent with Navigation and Interaction in Unity Using NavMesh and C#
Instructor-led OR Self-paced course + Official exam + Digital badge
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Requirements
Basic knowledge of programming, game design fundamentals, and core mathematical concepts is recommended. Ideal for learners with an interest in AI principles, algorithmic thinking, and creative problem-solving to design intelligent, dynamic, and interactive game experiences.
Target Audience
Duration
Instructor-Led: 1 day (live or virtual)
Self-Paced: 8 hours of content
The EK Academy
Redefining professional excellence through intentional, intellectual learning experiences
