Large amounts of data containing sensitive personal information are being constantly collected in today's digitized world. This course aims at providing students with a solid understanding of a set of core and emerging techniques for privacy-preserving data analytics. Topics include data anonymization techniques, differential privacy, multi-party computation protocols, zero-knowledge proofs, privacy-preserving machine learning algorithms, and encrypted databases and searchable encryption schemes. Learning activities include lectures, tutorials, case studies, and assignments.

For a student to pass the course, at least 30% of the maximum mark for the examination must be obtained.