Attendees of this hybrid event will gain a practical and beginner-friendly introduction to Federated Learning, a privacy-preserving approach to AI that allows model training without centralizing data. Through Dr. Chong Shen Ng's talk, participants will learn how federated learning addresses challenges in data access and privacy, explore key concepts, and see real-world code examples using the open-source Flower framework. The session will highlight how techniques like differential privacy and secure aggregation enhance security and how Flower simplifies building scalable, distributed AI systems.