Courses

Our lab offers several courses for undergraduate and/or graduate students.

Courses given in the current semester (Winter 2026-2027)

Selected Topics on Deep Learning over Structured Data 02360028

Prof. Benny Kimelfeld

Machine learning over relational databases, tables and graphs: feature engineering, vector embeddings, graph neural networks, transformer-based foundation models, and explainability.
Data Management Algorithms for Decision 02360771

Prof. Brit Youngmann

Data management algorithms for reliable decision making: integrating, cleaning and investigating data so that sound conclusions can be drawn from it, in the presence of missing values, inconsistency and bias.
Databases 02360363

Prof. Hagit Attiya

The theory and practice of database management: the relational and logical models, SQL, relational algebra and calculus, entity-relationship design and normal forms, and semi-structured data.

Advanced Topics in Computer Science 5 02360605

Prof. Benny KimelfeldSpring 2026

The structured-data machine learning course under the Advanced Topics umbrella number: learning over tables, graphs and relational databases, from feature engineering and vector embeddings to graph neural networks and transformer-based foundation models.
Topics in Seminar on Responsible Data 02360010

Prof. Brit YoungmannSpring 2026

A seminar on responsible data management — bias removal, fairness and privacy — read through recent papers in the field and presented by the participants.
Databases 02360363

Prof. Brit YoungmannSpring 2026

The theory and practice of database management: the relational and logical models, SQL, relational algebra and calculus, entity-relationship design and normal forms, and semi-structured data.
Data Management Algorithms for Decision 02360771

Prof. Brit YoungmannWinter 2025-2026

Data management algorithms for reliable decision making: integrating, cleaning and investigating data so that sound conclusions can be drawn from it, in the presence of missing values, inconsistency and bias.