HIOK0002FU Language Processing 2

Volume 2022/2023

IT and Cognition


Have you ever wondered how to build a system that can process text automatically, for example translate between languages, reveal syntactic structure, or extract semantic information?  

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, semantic and discourse analysis, and machine translation. 

The main focus will be on the practical implementation of methods for syntactic parsing. The format of the class consists of lectures (including guest lectures), student presentations, and project work.

Learning Outcome

Academic objectives

See the curriculum:


2015 curriculum
2019 curriculum

See all the curriculums.



  • Category
  • Hours
  • Class Instruction
  • 28
  • Preparation
  • 105
  • Exam Preparation
  • 73
  • Total
  • 206
Continuous feedback during the course
Feedback by final exam (In addition to the grade)
7,5 ECTS
Type of assessment
Written assignment
Type of assessment details
Take-home assignment, set subject
Marking scale
7-point grading scale
Censorship form
No external censorship

Take-home assignment, set subject