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Great work!

1. Great work!

Great work!

2. You have completed the course

You have completed the course, congratulations! During the course, you have learned a lot of concepts and applied many practical techniques.

3. Recap: What you have learned

You have learned about personally identifiable information, quasi-identifiers, linkage attacks, data suppression, masking, generalization, synthetic data generation, sampling from probability distributions for different types of attributes.

4. Privacy models: k-anonymity

You also learned how to reach a k-anonymous dataset, explored possible attribute combinations, and then generalized data using hierarchies and ranges to avoid re-identification attacks. All that without falsifying data!

5. Privacy models: differential privacy

You learned the key concept of differential privacy and how these systems can quantify privacy in data releases. All privacy-preserving techniques learned in the course have advantages, and differential privacy is one of the most important definitions in present time.

6. Differentially private models and operations

People are increasingly working with differentially private machine and deep learning models. And in this course, you have trained and ran different types of private models and practiced advanced concepts such as privacy budget and tracking.

7. Other interesting libraries

Other interesting libraries to learn about are Google differential privacy, TensorFlow Privacy, and ARX.

8. Congrats!

Thank you for completing the course. It's been a pleasure working with you and I wish you the best of luck in your journey.