Data Security and Privacy

The course introduces security and privacy challenges in the data life cycle. Concepts of threat models, secure computation, privacy-preserving data processing, as well as security issues related to machine learning are introduced. On completion of the course, you should be able to: * analyze security and privacy considerations in a typical data life cycle * explain and compare algorithmic, technical, and physical measures for secure and privacy-preserving data science * discuss the trade-offs and limits of secure and privacy-preserving data science * reflect on the legal and ethical issues of a data science scenario.