Machine Translation (Master's Level)

7.5 credits

Syllabus, Master's level, 5LN711

Education cycle
Second cycle
Main field(s) of study and in-depth level
Language Technology A1N
Grading system
Fail (U), Pass (G), Pass with distinction (VG)
Finalised by
The Department Board, 1 March 2024
Responsible department
Department of Linguistics and Philology

Entry requirements

A Bachelor's degree and (1) 60 credits in language technology/computational linguistics, or (2) 60 credits in computer science, or (3) 60 credits in a language subject, 7.5 credits in computer programming and 7.5 credits in logic/discrete mathematics. Also required is 7.5 credits in machine learning, and proficiency in English equivalent to the general entry requirements for first-cycle (Bachelor's level) studies.

Learning outcomes

For the grade Pass, after completing the course the student should be able to

  1. explain, apply, and critically assess manual and automatic evaluation methods for machine translation
  2. analyse and critically review scientific publications in the field of machine translation
  3. describe and critically discuss the architecture of machine translation systems and assessment of machine translation systems
  4. independently build translation models on their own, using existing tools and evaluate and analyse the translation results
  5. compare different types of machine translation strategies, such as rule-based, statistical, and neural machine translation
  6. implement components of machine translation systems or components used in evaluation or preprocessing.
  7. plan and carry out research tasks based on sound methodological principles and within the given time limits.


The course provides an overview of different types of machine translation systems with a focus on architecture, usage and evaluation.


The teaching consists of lectures and laboratory sessions under supervision.


Examination takes place through oral and written presentation of assignments. Details about the examination are provided at the start of the course.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator.