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729G17 Language Technology


Language technology – technology for the analysis and interpretation of natural language – forms a key component of smart search engines, personal digital assistants, and many other innovative applications. The goal of this course is to give an introduction to language technology as an application area, as well as to its basic methods. The course focuses on methods that process text.

Intended learning outcomes

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

  1. explain basic methods for the analysis and interpretation of words, sentences, and texts
  2. practically apply language technology methods and systems to texts and text collections
  3. evaluate language technology components and systems using standard validation methods
  4. judge the difficulty and the feasibility of language technology applications

For each intended learning outcome, there is a set of knowledge requirements that describe what you need to demonstrate in order to earn a certain grade. These knowledge requirements are listed on the Examination page.

Course content

The course covers

  • basic methods and techniques for the analysis and interpretation of words, sentences, and texts
  • language technology systems
  • validation methods
  • tools, software libraries, and data

in the following areas: text classification, language modelling, part-of-speech tagging, syntactic analysis, and semantic analysis.

We have structured the course content into concepts and procedures. By concepts we mean terms and models that you should be able to explain and apply. By procedures we mean standard tasks that you should be able to perform. If a concept or procedure is classified as advanced, it is beyond what is being expected from you for a passing grade.

Teaching and working methods

The course is taught in the form of lectures, lab sessions, and seminars in connection with a final project. You are also expected to study independently, both individually and in groups. When you plan your time for the course, you should calculate approximately

  • 53 hours to prepare for, attend, and revise the lectures
  • 53 hours to prepare for, carry out, and reflect on the labs
  • 53 hours to plan, carry out, and reflect on the project

The course is co-taught with TDP030 Language Technology on the Bachelor’s programme in Innovative Programming.

Course literature

The reading for this course consists of individual sections from the following book:

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, December 2020.

For follow-up and in-depth reading, we recommend the following books:

Feedback policy

What you can expect from us. We try our best to give you prompt, constructive, and meaningful feedback on how well you meet the knowledge requirements set out for the course. We offer feedback in various forms; you can find detailed information about this on the Examination page. Our focus is on non-examinatory, formative feedback, which you can use to improve your learning (and we can use to improve our teaching!) while the course is ongoing.

What we expect from you. We expect you to familiarise yourself with the knowledge requirements set out for the course, and to actively seek our feedback on how well you meet these requirements. We also expect you to reflect on the feedback that we provide, and to grasp opportunities to put it to good use.

Communication policy

What we expect from you. This webpage is the primary source of information about the course, and we expect you to keep yourself up-to-date with what we publish here. We also send out information via the University’s email list for the course, and we expect you to read email from this list on a regular basis while the course is ongoing.

What you can expect from us. When you contact us via email, you can expect an answer during standard working hours, 8–17. (We do not respond to email in the evening or on a weekend.) For a more personal contact, you can drop in during the examiner’s office hours (Thursdays 10:15-12 in building E, room 3G.476) or book an appointment.


Page responsible: Marco Kuhlmann
Last updated: 2021-01-15