120 credits including a second course in programming. Participation in a course in machine learning. Proficiency in English equivalent to the Swedish upper secondary course English 6.
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.
