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Interactive Lecture Notes, Slides and Exercises for the NLP course at DIKU, UCPH

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Natural Language Processing (NDAK18000U)

Course at the University of Copenhagen

Materials from this interactive book are used throughout the Natural Language Processing course at the Department of Computer Science, University of Copenhagen. The official course description can be found here. Materials covered each week are listed below. The course schedule and materials are tentative and subject to minor changes. Most reading material is from Speech and Language Processing by Jurafsky & Martin.

Week Reading (before lecture) Lecture (Tuesday) Lab (Friday & Monday) Lab notebook
36 Chapter 2
Chapter 4
1. Sep. 2026:
Course Logistics (slides)
Introduction to NLP (slides)
Tokenisation & Sentence Splitting (notes, slides, exercises)
Text Classification (slides)
4. & 7. Sep. 2026:
Google Colab and notebook workflow
BPE algorithm and subword tokenisation
Introduction to PyTorch
Project group arrangements
Questions about the course project
lab 1
37 Chapter 18 8. Sep. 2026:
Sequence Labelling (slides)
11. & 14. Sep. 2026:
Sequence labelling and beam search
Project help
lab 2
38 Chapter 3
Chapter 5
15. Sep. 2026:
Language Modelling (slides)
Word Embeddings (slides)
18. & 21. Sep. 2026:
Word representations and sentiment classification
Project help
lab 3
39 Chapter 6
Chapter 14
22. Sep. 2026:
Recurrent Neural Networks (slides)
Neural Language Models (slides)
25. & 28. Sep. 2026:
Error analysis and explainability
Project help
lab 4
40 Chapter 7
Chapter 9
29. Sep. 2026:
Attention (slides)
Transformers (slides)
2. & 5. Oct. 2026:
Language Models with Transformers and RNNs
Project help
lab 5
41 Chapter 21
Chapter 11, Section 11.6
Clark et al., 2020
6. Oct. 2026:
Information Extraction (slides)
Question Answering (slides)
9. & 19. Oct. 2026:
In-depth look at Transformers and Multilingual QA
Project help
lab 6
43 Xu et al., 2026
Weidinger et al., 2023
20. Oct. 2026:
Human Label Variation and Pluralistic Aignment (tba)
Sociotechnical Audit of AI Safety (tba)
23. & 26. Oct. 2026: Project help. lab 7
44 Chapter 20
Chapter 13
27. Oct. 2026:
Parsing (slides)
Machine Translation (slides)
30. Oct. 2026: Project help.
The easiest way to view the course content is via the static [nbviewer](https://nbviewer.jupyter.org/github/coastalcph/nlp-course/blob/master/overview.ipynb). To be able to make changes to the book and render it dynamically, see the [installation instructions](INSTALL.md).

About

Interactive Lecture Notes, Slides and Exercises for the NLP course at DIKU, UCPH

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