The IRLAb staff is involved with teaching in the Artificial Intelligence and Information Studies programs. Within the MSc AI program, IRLab staff is mostly responsible for the courses related to Information Retrieval. More information on the MSc AI program can be found in the Course Catalogue.

University of Amsterdam students who like to do a thesis project with a member from IRLab can find our projects at datanose or apply through this form.

Courses taught (fully or in part) by IRLab members (unless stated otherwise all courses are University of Amsterdam courses; Sem n/per m is short for Semester n/period m):

• 2022-2023
  • Information Retrieval 1 (MSc AI, Yates, Sem 2/per 4)
  • Information Retrieval 2 (MSc AI, 6EC, Kanoulas, Sem 1/per 1)
  • Language technology (MBA, 6EC, Kanoulas, Sem 2/per 2)
  • Master Thesis AI (MSc, 48 EC, all IRLab staff, throughout the year), as daily supervisors
  • Master Thesis IS (DS) (MSc, 18EC, all IRLab staff, Sem 1/per 2-Sem 2/per 6), as daily supervisors
  • Network Science (BSc, 6EC, Marx, Sem 1/per 2)
  • Project AI A and B (MSc, 6 EC, all IRLab staff, throughout the year), as daily supervisors
  • Recommender Systems (MSc AI, 6EC, Ariannezhad and De Rijke, Sem 2/per 6)
  • Toegepaste Machine Learning (BSc, 6EC, Marx, Sem2/per2)
  • Zoekmachines (BSc, 6EC, Alian Nejadi, Sem1/per 1)

• 2021-2022
  • Applied Machine Learning (BSc, 6 EC, Kanoulas, Sem 2/per 5)
  • Data Science (BSc, 6EC, Marx, Sem 2/per 4)
  • Information Retrieval 1 (MSc AI, Yates, Sem 2/per 4)
  • Information Retrieval 2 (MSc AI, 6EC, Kanoulas, Sem 1/per 1)
  • Language technology (MBA, 6EC, Kanoulas, Sem 2/per 2)
  • Machine Learning and Neural Approaches for Information Retrieval (Part 1) (ESSIR 2022 tutorial, Yates)
  • Master Thesis AI (MSc, 48 EC, all IRLab staff, throughout the year), as daily supervisors
  • Master Thesis IS (DS) (MSc, 18EC, all IRLab staff, Sem 1/per 2-Sem 2/per 6), as daily supervisors
  • Netwerkanalyse (BSc, 6EC, Marx, Sem 1/per 2)
  • Project AI A and B (MSc, 6 EC, all IRLab staff, throughout the year), as daily supervisors
  • Towards Reproducible ML Research in Information Retrieval (SIGIR 2022 tutorial, Lucic, Bleeker, De Rijke, Sinha, Jullien, Stojnic)
  • Towards Reproducible ML Research in Natural Language Processing (ACL 2022 tutorial, Lucic, Bleeker, Bhargav, Zosa Forde, Sinha, Dodge, Luccioni, Stojnic)
  • User Models and Interactive IR (ESSIR 2022 tutorial, Deffayet, De Rijke)
  • Zoekmachines (BSc, 6EC, Marx, Sem1/per 1)

• 2020-2021
  • Applied Machine Learning (BSc, 6 EC, Kanoulas, Sem 2/per 5)
  • Data science (BSc, 6EC, Marx, Sem 2/per 4)
  • Information Retrieval 1 (MSc, 6 EC, Markov, Sem 2/per 4)
  • Information Retrieval 2 (MSc, 6 EC, Kanoulas, Sem 1/per 1)
  • Fairness, Accountability, Confidentiality and Transparency in AI (MSc, 6 EC, De Rijke, Sem 1/per 3)
  • Knowledge and Data (BSc, 6EC, Marx, Sem 2/per 4)
  • Language technology (MBA, 6EC, Kanoulas, Sem 2/per 2)
  • Master Thesis AI (MSc, 48 EC, throughout the year), as daily supervisors
  • Master Thesis IS (DS) (MSc, 18EC, Marx, Sem 1/per 2-Sem 2/per 6), as daily supervisors
  • Network analysis (BSc, 6EC, Marx, Sem 1/per 2)
  • Project AI A and B (MSc, 6 EC, throughout the year), as daily supervisors
  • Zoekmachines (BSc, 6EC, Marx, Sem 1/per 1)