Lesson 1
Introducing Differential Privacy
In this lesson, you'll learn about the basics of differential privacy, a method for measuring how operations impact the privacy of data.
Course
Learn three cutting-edge technologies for privacy-preserving AI: Federated Learning, Differential Privacy, and Encrypted Computation.
Learn three cutting-edge technologies for privacy-preserving AI: Federated Learning, Differential Privacy, and Encrypted Computation.
Last Updated June 22, 2023
No experience required
Lesson 1
Introducing Differential Privacy
In this lesson, you'll learn about the basics of differential privacy, a method for measuring how operations impact the privacy of data.
Lesson 2
Evaluating the Privacy of a Function
In this lesson, you'll implement differential privacy in Python.
Lesson 3
Introducing Local and Global Differential Privacy
Learn how to apply differential privacy to arbitrary algorithms by adding noise to the outputs.
Lesson 4
Differential Privacy for Deep Learning
Learn how we can apply differential privacy to deep neural networks.
Lesson 5
Federated Learning
Learn about federated learning, a method for preserving data privacy by training models where the data lives.
Lesson 6
Securing Federated Learning
Secure models trained using federated learning with multi-party computation.
Lesson 7
Encrypted Deep Learning
Learn how to perform encrypted computation. Build an encrypted database, and generate an encrypted prediction with an encrypted neural network on an encrypted dataset.
Andrew Trask
Leader of OpenMined, Research Scientist at DeepMind Oxford, PhD Student
Andrew Trask
Leader of OpenMined, Research Scientist at DeepMind Oxford, PhD Student
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