AI+ Gaming™ - eLearning (exam included)
275,00 EUR
- 16 hours
Unlock the power of artificial intelligence to create immersive, adaptive, and next‑generation gaming experiences with the AI+ Gaming™ Certification. This industry‑aligned program empowers you to blend creativity with cutting‑edge AI, building real‑world game projects that bring smarter worlds, characters, and player interactions to life
Key Features
Language
Course and material in English
Level
Beginner-Intermediate level
Access
1 year access to the platform 24/7
8 hours of video lessons & multimedia
16 hours of study time recommendation
eBooks, Audiobooks, Podcasts
Quizzes, Assessments, and Course Resources
Exam
Online Proctored Exam with One Free Retake
Certificate
Certification of completion included
Shape the Future of Intelligent Game Design
Learn how artificial intelligence is reshaping game design, player interaction, and virtual worlds by building real-world gaming projects with advanced AI tools.
Learning Outcomes
At the end of this course, you will be able to:
AI-Powered Game Design
Integrate AI into gameplay mechanics, storytelling, and player interactions.
Procedural Content Creation
Use AI algorithms to generate dynamic levels, characters, and virtual worlds.
Player Behavior Analytics
Analyze player data to personalize experiences and boost engagement.
Reinforcement Learning & Intelligent NPCs
Develop adaptive agents that learn and respond realistically in games.
Game Engine Integration
Apply AI models hands-on in popular engines like Unity and Unreal for practical, real-world projects
Course timeline
Introduction to AI in Games
Lesson 1
Learn what AI is, its evolution in gaming, types of game AI, and key benefits, challenges, and innovations.
Game Design Principles with AI
Lesson 2
- Explore game mechanics, player experience, and how AI shapes gameplay, narrative, and environment interactions.
- Case Study: Dynamic AI in Middle-earth: Shadow of Mordor.
- Hands-On: Design adaptive NPC behavior and environment interactions.
Foundations of AI in Gaming
Lesson 3
- Cover core AI concepts, search algorithms, pathfinding, AI behavior modeling, procedural content generation, and introductory machine learning & reinforcement learning.
- Case Study: AI in Minecraft.
- Hands-On: Implement A* pathfinding and FSM for NPC behavior.
Reinforcement Learning Fundamentals
Lesson 4
- Learn states, actions, rewards, policies, Q-learning, exploration vs. exploitation, and methods like DQN and policy gradients.
- Case Study: Reinforcement learning in DeepMind’s AlphaGo.
- Hands-On: Train a reinforcement learning model on OpenAI Gym’s GridWorld.
Planning and Decision Making
Lesson 5
- Master Minimax, Alpha-Beta pruning, Monte Carlo Tree Search, and applications in board games and RTS games.
- Case Study: Strategic AI in StarCraft II.
- Hands-On: Implement Minimax for Tic-Tac-Toe.
AI in 2D/3D Game Environments
Lesson 6
- Understand environment representation, navigation, pathfinding, and behavior systems in virtual spaces.
- Case Study: AI in The Legend of Zelda: Breath of the Wild.
- Hands-On: Build basic navigation and interaction in 2D/3D environments.
Adaptive Systems & Dynamic Difficulty
Lesson 7
- Explore adaptive systems, dynamic difficulty adjustment, AI-driven storytelling, player profiling, and implementation strategies.
- Case Study: Left 4 Dead’s AI Director for dynamic enemy management.
- Hands-On: Develop an adaptive difficulty system in Unity.
The Future of AI in Gaming
Lesson 8
Discover generalist AI agents, transfer learning, AI-powered design/testing tools, ethical AI considerations, and emerging VR/AR and esports AI applications.
Tools explored
- 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
Who Should Enroll in this Program?
Aspiring Game Developers: For those wanting to incorporate AI into game design and development.
AI Enthusiasts: Ideal for learners curious about how AI influences gameplay and player interactions.
Game Designers: Perfect for creatives looking to use AI for storytelling, dynamic worlds, and adaptive gameplay.
Software Engineers: Suited for professionals applying programming and AI techniques in the gaming industry.
Students & Researchers: Valuable for anyone studying AI, machine learning, or interactive entertainment.
More Details
Prerequisites
- Basic Programming Skills: Comfortable coding in Python or a similar language.
- Foundational Math Knowledge: Understanding of linear algebra and probability.
- Introductory Machine Learning: Familiarity with ML concepts and algorithms.
- Game Development Experience: Basic knowledge of Unity or Unreal Engine.
- Problem-Solving Mindset: Ability to tackle challenges creatively and logically.
Exam Details
- Duration: 90 minutes
- Passing :70% (35/50)
- Format: 50 multiple-choice/multiple-response questions
- Delivery Method: Online via proctored exam platform (flexible scheduling)
- Language: English
Licensing and accreditation
This course is offered by AVC according to Partner Program Agreement and complies with the License Agreement requirements.
Equity Policy
AVC does not provide accommodations due to a disability or medical condition of any students. Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.
Frequently Asked Questions
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