Klassikaal
1 dag
AI+ Game Design Practitioner™
Formerly known as AI+ Gaming™
Discover how AI transforms game design, player engagement, and virtual environments. Build real-world gaming projects using cutting-edge AI technologies.
- Comprehensive Skill Development
Master AI-driven game design, adaptive storytelling, and intelligent NPC development to create immersive, data-enhanced gaming experiences. - Industry Recognition
Earn a globally recognized certification that validates your expertise in integrating artificial intelligence within modern gaming environments. - Hands-On Learning
Work on real-world gaming projects, from AI-based character behavior modeling to predictive player analytics, enhancing creativity and technical precision. - Career Advancement
Unlock career opportunities in game development, AI simulation design, virtual production, and interactive entertainment industries. - Future-Ready Expertise
Stay at the forefront of gaming innovation with cutting-edge knowledge in generative AI, immersive simulations, and intelligent gameplay systems.
- Trainer uit de praktijk, uit ons netwerk van 200+ trainers
- Klassikaal op locatie of live virtueel te volgen
- Betalen op factuur, annuleren volgens heldere voorwaarden
- Ook incompany voor je hele team
Ruim 5.000 cursisten per jaar volgen een training bij ons
Erkend opleider en partner van
150+
AI-trainingen in ons aanbod
200+
trainers uit de praktijk
5.000
cursisten per jaar
20 jaar
ervaring in IT-opleidingen
Voor wie
Voor wie is deze training
Aspiring Game Developers – Ideal for those looking to integrate AI into game design and development.
AI Enthusiasts – Perfect for learners eager to explore how AI shapes gaming experiences and player interactions.
Game Designers – Suited for creatives aiming to use AI for storytelling, dynamic worlds, and adaptive gameplay.
Software Engineers – Great for professionals seeking to apply programming and AI techniques within the gaming industry.
Students & Researchers – Beneficial for those pursuing studies or research in AI, machine learning, or interactive entertainment.
De training
Dit leer je tijdens de training
Praktijkgericht, met een trainer die zelf in het veld werkt. Geen theorie om de theorie.
Na deze training
Wat deze training je oplevert
- Industry-Relevant Curriculum Gain expertise in AI-driven game design, player behavior modeling, and adaptive gameplay mechanics.
- Hands-On Learning Work on real gaming projects integrating AI for character behavior, world generation, and personalization.
- Career Advancement Boost your profile for roles in game development, AI engineering, and interactive entertainment design.
- Cutting-Edge Tools Learn to use leading AI frameworks and gaming engines to develop immersive, intelligent experiences.
- Global Recognition Earn a certification that validates your AI and gaming skills with credibility across the tech and gaming industries.
Inhoud
Het programma
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 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
Module 9: Capstone Project
Tools you will explore
- Unity ML-Agents
- TensorFlow
- PyTorch
- Python
- OpenAI Gym
- Blender
- NVIDIA DeepStream
- Reinforcement Learning Frameworks
- Natural Language Processing Libraries
- Computer Vision SDKs
- Game Data Analytics Tools
- Behavior Tree Editors
Praktisch
Goed om te weten
Lesmethode
Kenmerken
Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam
Access to all materials and exams is provided for 365 days after delivery.
Voorkennis
- Requires basic programming knowledge in Python, understanding of linear algebra and probability, familiarity with machine learning concepts, and experience with Unity or Unreal Engine. Also, a creative problem-solving mindset is essential.
Inschrijven
Alles op een rij
AI+ Game Design Practitioner™
- Betalen op factuur mogelijk
- Verschuiven of annuleren volgens onze voorwaarden
- Ook incompany voor je hele team via maatwerk
Zekerheid
Inschrijven zonder verrassingen
Heldere voorwaarden
Verschuiven of annuleren doe je volgens onze algemene voorwaarden. Geen kleine lettertjes achteraf.
Hulp bij je keuze
Twijfel je of dit de juiste training is voor jouw rol of team? Stel je vraag, we denken met je mee.
Ook incompany
Elke training kan op maat voor je hele team, bij jullie op locatie of virtueel. Lees meer.
Veelgestelde vragen
Vragen over deze training
Kan ik de training ook virtueel volgen?
Veel trainingen volg je live als Virtual Classroom Training. Je zit dan vanuit huis of kantoor online in de les, met dezelfde trainer. Bekijk de datumopties bij de inschrijving.
Wat als ik verhinderd ben op de gekozen datum?
Verschuiven naar een andere datum kan volgens onze algemene voorwaarden. Neem contact op met onze servicedesk, dan regelen we het samen.
Kunnen we deze training met het hele team volgen?
Ja. Voor teams verzorgen we trainingen ook incompany, afgestemd op jullie organisatie. Vraag een voorstel aan en we plannen een intake.
Kan mijn werkgever de training betalen?
Ja, betalen op factuur is mogelijk. Zo loopt de inschrijving eenvoudig via je werkgever. Heb je een afwijkend factuuradres of referentie nodig, dan geef je dat bij de inschrijving op.
Hoe weet ik of ik genoeg voorkennis heb?
Bij Goed om te weten op deze pagina staat welke voorkennis we aanraden. Twijfel je of deze training past bij jouw rol of niveau? Stel je vraag, we denken met je mee.
Klaar om te starten?
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