HIOK03598U  Language Processing 2

Volume 2017/2018

IT and Cognition


In this class we will explore fundamental algorithms and models for natural language processing, and describe the application of these algorithms and models to key problems in natural language processing, such as POS tagging, syntactic parsing, and sentiment analysis.
The format of the class consists of lectures and project work.

The examinee is able to:

  • demonstrate theoretical insight into natural language processing by

identifying problems and solutions in the context of practical applications

  • apply feature extraction methods and modelling techniques in natural

language processing

  • deal with specific challenges arising from processing user-generated


  • evaluate systems or system components.


Learning Outcome

Competence objectives:

Look in the current curriculum, which in this case may be: 



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7,5 ECTS
Type of assessment
Written examination
Written take-home assignment
Marking scale
7-point grading scale
Censorship form
No external censorship
  • Category
  • Hours
  • Class Instruction
  • 28
  • Course Preparation
  • 105
  • Exam Preparation
  • 73
  • Total
  • 206