Data Privacy and Anonymization in R

With big data and social media, data privacy is becoming a major concern. Google, Apple, US Census Bureau and other organizations have started to advocate better privacy techniques, particularly differential privacy. This is a mathematical condition that quantifies privacy risk. This course will teach you how to code basic data privacy methods as well as a differentially-private algorithm that is based on different differentially private properties. You can use these tools to create basic synthetic data sets (fake data), with the differential privacy guarantee, which allows public data release.