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Foundations of NLP

Veranstaltungstyp: Seminar

Ort: 93/E06

Zeiten: Termine am Montag, 23.03.2026 12:00 - 18:00, Dienstag, 24.03.2026 09:00 - 12:00, Dienstag, 24.03.2026 13:00 - 16:00, Mittwoch, 25.03.2026 09:00 - 12:00, Mittwoch, 25.03.2026 13:00 - 16:00, Donnerstag, 26.03.2026 09:00 - 12:00, Donnerstag, 26.03.2026 13:00 - 16:00, Freitag, 27.03.2026 09:00 - 12:00, Freitag, 27.03.2026 13:00 - 16:00

Beschreibung: Course Description:
This intensive one-week course provides a hands-on introduction to modern natural language processing (NLP) using deep learning. Students will learn the fundamentals of core NLP tasks and neural architectures, with a particular emphasis on attention mechanisms and the inner workings of transformer models. The course culminates with an overview of large language models (LLMs), providing a solid foundation for understanding current trends and preparing students for more advanced topics in NLP.

Key topics include:
- Fundamentals of NLP tasks (e.g., classification, sequence labeling, machine translation)
- Word embeddings and contextual representations
- Recurrent and convolutional architectures in NLP
- Attention mechanisms and the transformer architecture
- Pretraining strategies: masked language modeling, autoregressive modeling
- Introduction to large language models and their capabilities

Learning Objectives:
By the end of this course, students will...

… understand key NLP tasks and the neural architectures used to address them.
… be able to explain and implement attention mechanisms and transformer-based models.

Prerequisites:
Solid background in Linear Algebra and Calculus is required.
Some experience with Python and machine learning is recommended, but not mandatory.

Course Format:
Delivery Method: in-person

Type of Contact & Contact Hours: intensive block course (daily sessions over one week)

Selection Process: None

Assessment and Grading:
- Active participation in lectures
- Group presentation
- Short written report on a selected NLP topic or model

Required Texts and Materials or Further Resources:
Key readings and code examples will be provided during the course via Stud.IP or direct links

Students will work with open-source tools and models (e.g., HuggingFace Transformers)

Important Dates:
Registration Deadline on HisInOne/EXA: 23.03.2026
De-Registration Deadline on HisInOne/EXA: 03.04.2026

Will this class be offered again/regularly?
This course may be offered again, depending on instructor availability and demand. It is part of a rotating series of “Introductory and Advanced Topics in NLP.”