Data Privacy and Anonymization in R
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Course overview
- Provider
- Datacamp
- Course type
- Free trial availiable
- Deadline
- Flexible
- Duration
- 4 hours
- Certificate
- Available on completion
- Course author
- Claire Bowen
Description
Publicly release data sets with a differential privacy guarantee.
With social media and big data everywhere, data privacy has been a growing, public concern. Recognizing this issue, entities such as Google, Apple, and the US Census Bureau are promoting better privacy techniques; specifically differential privacy, a mathematical condition that quantifies privacy risk. In this course, you will learn to code basic data privacy methods and a differentially private algorithm based on various differentially private properties. With these tools in hand, you will learn how to generate a basic synthetic (fake) data set with the differential privacy guarantee for public data release.
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