Overview

Published

July 12, 2024

Natural Language Processing (NLP) develops methods for making human language accessible to computers. This course aims to provide you with a solid understanding of the models and algorithms that power modern NLP and with practical experience in applying them to realistic problems. The course focuses on methods based on deep learning.

Learning outcomes

On completion of the course, you will be able to:

  • explain central concepts, models and algorithms in NLP
  • implement NLP methods and apply them to realistic problems
  • evaluate NLP components and systems using appropriate methods

Course content

The course covers the following content:

  • Introduction to natural language processing
  • Statistical and neural language models
  • Word representations, such as word2vec
  • Syntactic and semantic analysis
  • Neural network architectures, such as RNNs and Transformers
  • Large language models, such as ChatGPT
  • Program libraries and datasets
  • Evaluation methods
  • Current research and development

Course format

The teaching materials for this course consist of pre-recorded video lectures and coding exercises. Throughout the course, there are three mandatory online meetings and an optional evaluation meeting:

  • Meeting 1: 2024-09-04, 18:00–20:00
  • Meeting 2: 2024-10-02, 18:00–20:00
  • Meeting 3: 2024-11-20, 18:00–20:00
  • Optional evaluation meeting: 2025-01-15, 18:00–20:00

Between these meetings, you can work with the teaching materials at your own pace. If you need help or want feedback, you can contact us via email or chat or book an appointment.

When you plan your time for the course, you should expect to spend approximately

  • 10 hours to prepare for and attend the online meetings
  • 30 hours to watch the video lectures and work on the quizzes
  • 40 hours to prepare for and work on the coding exercises

Course literature

Natural language processing is a fast-moving field, and there is currently no single textbook that covers the course content. As a side reading, we recommend the following work in progress:

Daniel Jurafsky and James H. Martin. Speech and Language Processing. An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Draft chapters in progress, February 2024.