Dates
| weekly | Thursday | 10:15 - 11:45 | 12.10.2026 - 29.01.2027 | C 14.103 Seminarraum |
| single appointment | Mo, 08.03.2027, 10:30 - Mo, 08.03.2027, 13:00 | C 3.120 Seminarraum |
Curriculum context
written test 90 min. (50%)
Resit date: No resit date will be offered to this assessment, because it is didactically inseparably connected with one of the associated courses. A resit will only be possible, if the module is available again.
Organizational information
Registration
Die Anmeldung beginnt erst am 02.10.2026 um 08:00 Uhr. Sie endet am 12.10.2026 um 23:59 Uhr
Persons
Content
The course introduces Natural Language Processing (NLP), classic models such as RNNs, and proceeds to modern models such as Transformers. Pre-trained and large language models (LLMs) are introduced and rounded off with Retrieval Augmented Generation (RAG).
In later half of the course, Knowledge Graphs (KGs) will be introduced, and how RAG techniques can be used to perform Question Answering (QA) over Knowledge Graphs using LLMs.
The goal is to introduce NLP to students, and quickly bring them to the modern landscape of LLMs. The focus on LLMs is to teach students how to build QA systems over text data and also knowledge graphs.
Evaluation
Further information on teaching evaluation: https://www.leuphana.de/en/teaching/quality-management/evaluation/course-evaluation.html