Federated & Privacy Preserving Biomedical ML — Hands-on

Design and deploy privacy-first ML workflows across hospitals, labs, and devices. This module covers the federated learning (FL) stack—algorithms, systems, and privacy tech—so you can collaborate on biomedical models without centralizing sensitive data. You will implement secure training, evaluate privacy/utility trade-offs, and generate compliance-ready artifacts.