Become a data scientist and statistician capable of studying data you do not own and cannot see. Learn every major privacy-preserving technique to an intermediate level, understand how they work together, and how you can use them to safely study data owned by another organization (such as another university, enterprise, or government) without ever seeing the underlying data yourself.

By the end of the course you will be able to:

• Build privacy-preserving technologies from scratch
• Use federated learning to work with protected data on remote devices
• Understand the math behind encrypted computations
• Use differential privacy budgeting with PyTorch models