Data Privacy

Education facts

Code: 5DV241

In the information age, information is continuously stored and transmitted. Most of this information is sensitive, and needs to be properly processed and stored to avoid undesirable disclosure. Data-driven models and data aggregates are not free from privacy risks. Data privacy is the field that provides tools to avoid or control information leakage. This course aims to present privacy models  (computational definitions of privacy), techniques, and performance measures for privacy-preserving tools. During the course, the students will acquire knowledge about alternative perspectives of privacy as well as their implementation.

Entry requirements

At least 90 ECTS. At least 30 ECTS Computing Science, including 7.5 ECTS programming and 7.5 ECTS datastructures and algorithms; at least 22.5 ECTS mathematics, including 7.5 ECTS statistics and 7.5 ECTS calculus. The course assumes the students have been introduced to machine learning, for example by a course on artificial intelligence. Proficiency in English equivalent to the level required for basic eligibility for higher studies.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Data Privacy

  Umeå University

  Start date: 31 August 2026

  End date: 1 November 2026

  Pace of study: 50 %