Modul

Siehe Teilleistung.

Die Studenten lernen komplexe wissenschaftliche Themengebiete zu verstehen, zu hinterfragen und veröffentlichte
Resultate zu reproduzieren und zu überprüfen. Die Studenten erlangen ein vertieftes Wissen im Bereich des Interaktive Lernens und Erfahrung mit dem Einsatz von neuartigen Lernverfahren.

Siehe Teilleistung.

Each student will select a topic in the field of Interactive Learning and/or Explainable Artificial Intelligence. The organizers will suggest topics but the students are welcome suggest relevant topics. The students will then implement and evaluate several algorithms corresponding to the chosen topic. The experimental evaluation will be documented in a report and presented to their peers.
It is highly recommended to take this research project in combination with the “Interactive Learning” Seminar, where the students get the chance to acquire the required background on the literature.

We highly recommend to take this research project in combination with the “Interactive Learning” seminar.

It is highly recommended to attend the “Explainable Artificial Intelligence” lecture in parallel or prior to this project.

• Experience in Machine Learning is recommended, e.g. through prior coursework.
◦ The Computer Science Department offers several great lectures e.g., “Maschinelles Lernen - Grundlagen und Algorithmen” and “Deep Learning ”
• A good mathematical background will be beneficial
• Python experience is recommended
• We might use the PyTorch deep learning library In the exercises. Some prior knowledge in this is helpful but not necessary.

Arbeitsaufwand = 180h = 6 ECTS
• Präsenzzeit: 15h
• Projektarbeit: 135h
• Scientific Report schreiben + Päsentation vorbereiten: 30h