User privacy is of the utmost importance in our data-driven society. There are security concerns with traditional machine learning since it uses centralized data collection. A game-changing approach is federated learning, which enables models to train directly on consumers' devices while protecting their data.

In this session, we will explore how to use Swift to enable federated learning on iOS, allowing developers to create AI apps that prioritize user privacy.
Pupils are going to:
1. Discover the function of federated learning in AI that protects user privacy.
2. Find out the ins and outs of using Core ML and Swift to include federated learning.
3. While retaining data on-device, investigate practical uses like health monitoring and tailored suggestions.
4. Explore methods that may enhance federated learning on resource-constrained mobile devices.

This session is centered around a practical demonstration of the process for developing an iOS federated learning system. Discover state-of-the-art AI and mobile development with privacy as our top priority with this exclusive chance.