Assess graduate learners' ability to analyze policy, technical, and ethical trade-offs when deploying federated learning for cross‑institutional medical research; topics include privacy-preserving techniques (e.g., secure aggregation, differential privacy), data governance and consent models, regulatory compliance (HIPAA, GDPR), model utility versus privacy, adversarial and poisoning risks, interoperability and infrastructure constraints, auditability and accountability, and formulation of balanced policy and technical mitigation strategies through case‑based scenarios.