Federated Learning and Privacy-Preserving AI

Explains the Federated Learning (FL) paradigm, where models are trained locally on client data and only aggregated updates are shared. This pathway covers core privacy mechanisms like Differential Privacy.

After completing this Pathway, you will be able to:

• Identify a basic Federated Learning setup and it's components
• Describe how differential privacy secures model training