Certificate in Game AI: Data-Driven Design

• Introduction to Game AI – Covering the basics of artificial intelligence in game development, including its history and importance.
• Data-Driven Design – Exploring the concept of data-driven design, its benefits, and how it applies to game AI.
• Game AI Architecture – Examining the architecture of game AI, including the different components and their functions.
• Behavior Trees – Learning about behavior trees, a popular AI decision-making paradigm, and how to implement them in games.
• Pathfinding Algorithms – Diving into pathfinding algorithms, such as A\* and Dijkstra's, and their application in game AI.
• Machine Learning in Game AI – Exploring the use of machine learning techniques, such as neural networks and reinforcement learning, in game AI.
• Game AI Tools – Examining various game AI tools and middleware for rapid prototyping and development.
• Game AI Case Studies – Analyzing successful game AI implementations and the techniques used to achieve them.
• Ethical Considerations in Game AI – Discussing the ethical implications of using AI in games and how to approach them.