HIOK03598U Language Processing 2
Volume 2017/2018
Education
IT and Cognition
Content
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
content
- evaluate systems or system components.
Learning Outcome
Competence objectives:
Look in the current curriculum, which in this case may be:
MA-level:
2015-curriculum
All curricula are available here:
http://hum.ku.dk/uddannelser/aktuelle_studieordninger/it_cognition
Teaching and learning methods
Lectures
Workload
- Category
- Hours
- Class Instruction
- 28
- Course Preparation
- 105
- Exam Preparation
- 73
- Total
- 206
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Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Written examinationWritten take-home assignment
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Course information
- Language
- English
- Course code
- HIOK03598U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 4
- Schedule
- A
- Study board
- Study Board of Scandinavian Studies and Linguistics
Contracting department
- Department of Scandinavian Studies and Linguistics
Course Coordinators
- Jürgen Wedekind (9-6f7c6a696a706e7369456d7a7233707a336970)
Lecturers
Lecturers Jürgen Wedekind, Manex Agirrezabal
Saved on the
24-11-2017