HIOK0002FU Language Processing 2
Volume 2024/2025
Education
IT and Cognition
Content
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.
Teaching and learning methods
Lectures
Workload
- Category
- Hours
- Class Instruction
- 28
- Preparation
- 105
- Exam Preparation
- 73
- Total
- 206
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Exam
- Credit
- 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
- Re-exam
Take-home assignment, set subject
Course information
- Language
- English
- Course code
- HIOK0002FU
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 semester
- Placement
- Spring
- Schedule
- C1
Study board
- Study Board of Nordic Studies and Linguistics
Contracting department
- Department of Nordic Studies and Linguistics
Contracting faculty
- Faculty of Humanities
Course Coordinators
- Patrizia Paggio (6-74656b6b6d73446c7971326f7932686f)
- Manex Aguirrezabal Zabaleta (18-4f6370677a304369776b7474677c6364636e426a776f306d7730666d)
Saved on the
27-08-2024