Natural language processing (NLP) is the study of computational models of human language, with the ultimate goal of enabling machines to understand and use human language. Due to the presumed connection between human intelligence and human language use, NLP is a core field within artificial intelligence (AI) and currently the focus of significant scientific research, technology development and public interest. The advent of deep learning - and in particular Large Language Modelling (LLM) - has seen progress in NLP accelerate over the past years, with numerous major scientific breakthroughs.
This class provides an in-depth introduction to the field of NLP. We will introduce a range of different NLP tasks such as information extraction, document classification, sequence labelling, machine translation and question-answering, and use these tasks to discuss common challenges and solutions in NLP. This will include methods to learn word and sentence representations, as well as neural architectures for NLP. We will also spend significant time with Large Language Models (LLMs) and current research directions.
Since deep learning is now crucial to NLP, the course will include an introduction into the deep learning framework PyTorch. Students will put the covered topics into practice in weekly implementation assignments in Python.
Es kann nur entweder dieses Modul oder das Modul "Introduction to Natural Language Processing" eingebracht werden.
Die Veranstaltung wurde 1 mal im Vorlesungsverzeichnis WiSe 2025/26 gefunden:
