AI+ Game Design Agent Specialty™

Course code: NPAP6012

Formerly known as AI+ Game Design Agent™

Empower creators with AI+ Game Design Agent Specialty™ to craft intelligent, dynamic, and immersive gaming experiences.

  • Complete Skill development: Gain mastery in AI-enhanced game creation through procedural content, responsive storytelling, and intelligent NPC mechanics to produce engaging, evolving gaming environments
  • Internationally Acclaimed Credential: Secure a globally acknowledged certification that recognizes your ability to blend AI with innovative game building.
  • Practical Projects: Apply skills on authentic tasks like AI level creation, character dynamics, and player optimization to hone real-world design abilities.
  • Professional Growth Paths: Access roles in AI gaming, interactive prototyping, and simulation tech at studios, firms, and media outlets.
  • Next-Generation Industry Readiness: Advance confidently into the evolving era of gaming with comprehensive knowledge of generative AI, autonomous frameworks, and adaptive game architecture

Professional
and certified lecturers

Internationally
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and soft skills courses

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Course dates

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 285 EUR

Register

Starting date: Upon request

Guaranteed

Type: Self-paced

Course duration: 8 hours

Language: en

Price without VAT: 75 EUR

Register

Starting
date
Place
Type Course
duration
Language Price without VAT
G Upon request Self-paced 8 hours en 285 EUR Register
G Upon request Self-paced 8 hours en 75 EUR Register
G Guaranteed course

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Course description

AI-Powered Game Design

Learn to integrate artificial intelligence into game mechanics, storytelling, and player interactions for smarter gameplay.

Procedural Content Generation

Master techniques to create dynamic worlds, levels, and assets using AI-driven design tools.

Adaptive Gameplay & Player Modeling

Understand how to use data and AI to personalize player experiences and behaviors.

Intelligent NPC Development

Build non-player characters that think, learn, and respond realistically through machine learning and NLP.

Hands-On Game Integration

Apply AI frameworks in engines like Unity and Unreal to develop innovative, intelligent game prototypes.

Course structure

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

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

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

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

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

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#

Module 7: Future Trends in AI Game Design

  • 7.1 Current and Future AI Trends
  • 7.2 The Future of Generalist AI in Gaming
  • 7.3 Case Study

Module 8: Capstone Project

  • 8.1. Task Description
  • 8.2. Practical Implementation
  • 8.3. Testing and Debugging
  • 8.4. Hands-on

Prerequisites

  • Coding Essentials: Working knowledge of programming concepts and languages
  • Game Mechanics Basics: Awareness of fundamental game mechanics and structural design
  • Logic and Math Skills: Solid foundation in algorithms and reasoning.
  • AI Fundamentals: Basic comprehension of artificial intelligence concepts and frameworks
  • Imaginative Design Capability: Aptitude for conceptualizing interactive and dynamic gaming elements

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