Entry requirements

A Bachelor's degree and 60 credits in language technology/computational linguistics, or 60 credits in computer science, or 60 credits in a language subject, 7.5 credits in computer programming and 7.5 credits in logic/discrete mathematics. 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

• for a number of Natural Language Processing applications

1. explain the most common techniques used for such applications
2. explain and apply relevant evaluation methods
3. implement or make use of software for such applications

• analyse and critically review scientific publications on NLP applications
• explain basic ethical concepts and apply them to language technology tasks
• formulate guidelines for annotation, annotate data, compute inter-annotator agreement, train and evaluate a classifier in relation to an NLP task.

Content

The course provides an overview of Natural Language Processing applications with a focus on the classification of tokens and sentences. Emphasis is on basic techniques, evaluation methods and annotation.

Instruction

Teaching takes the form of lectures, lessons, seminars and laboratory sessions.

Assessment

Assessment takes place through written assignments and seminars with presentations and discussions.

Oral presentations and discussions are graded with U/G. Written assignments are graded either with U/G or U/G/VG. To receive the grade G for the course, a minimum of G must be achieved on all examinatory parts. The grade VG is rewarded when G has been achieved overall and VG has been achieved on at least 50% of the examinatory parts where the U/G/VG scale is applied. 

Details of the examination, including dates for written assignments and seminars as well as re-examination, are given 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.