Course provider: University of Primorska Faculty of Mathematics, Natural Sciences and Information Technologies (UP FAMNIT)
Instructors: Marko Tkalčič (UP FAMNIT)
Learning objectives: Participants will understand how recommender systems connect user behavior to algorithmic decisions, analyze how backend choices shape user experience, and critically evaluate personalization from technical, ethical, and societal perspectives.
Syllabus:
- what users experience vs. what systems do,
- the user model: a digital representation of a person,
- recommender systems: turning user models into suggestions,
- from interaction to feedback loop,
- measuring “good” recommendations,
- real-world applications: user experience meets infrastructure,
- trust, transparency, and user control,
- looking ahead: the future relationship between users and recommenders.