Computer Science, Second Cycle, Natural Language Processing, 3 credits

Learning outcomes

Knowledge and understanding
Completing this course gives the student the basic knowledge of Natural Language Processing (NLP), different methods, and learn how different natural language problems can be viewed, and solved.

Applied Knowledge and Skills
The student will learn how to solve different NLP problems, by deploying statistical and machine learning methods. The focus of this course is on deploying deep learning for various NLP problems.

Making judgments and attitudes
After completing this course, the student will be able to assess how deep learning methods of NLP is suitable for NLP problems. Analyzing problems, finding the correct methodology, and deploying techniques in different applications.

Content

The course will cover the following topics

NLP and its applications
Text structure analysis: Morphological, morpho-syntactic analysis, syntax, extraction and filtering
NN for NLP: Neural networks, sequential learning, tweaks and tunning neural networks
Text classification: Learning taxonomy, classification, learning regime, Metrics
Semantic space: Semantics of language, formal representation, vector representation, word embeddings
Sequence2Sequence: Neural machine translation, encode-decoder architecture, attention
Advanced Topics: Structure prediction, dialog and virtual assistants, combination of image and NLP, ethics in NLP.

Examinations and grades

Exercises, 3 credits (Code: A001)
Grades used are Fail (U), Pass (G) or Pass with Distinction (VG).

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may determine which grading system is to be used. The grade must be determined by a teacher specifically nominated by the university (the examiner).

In accordance with university regulations on grading systems for first and second-cycle courses and study programmes (Vice-Chancellor’s decision ORU 2018/00929), one of the following grades is to be used: fail (U), pass (G) or pass with distinction (VG). For courses included in an international master’s programme (60 or 120 credits) or offered to the university’s incoming exchange students, the A to F grading scale is to be used. The vice-chancellor, or a person appointed by them, may decide on exceptions from this provision for a specific course, if there are special grounds for doing so.

The grades used on this course are Fail (U), Pass (G) or Pass with Distinction (VG).

For students with a documented disability, the university may approve applications for adapted or other modes of assessment.

For further information, see the university's local examination regulations.

Specific entry requirements

At least 180 credits including 15 credits programming as well as qualifications corresponding to the course "English 5"/"English A" from the Swedish Upper Secondary School.

For further information, see the university's admission regulations.

Other provisions

The course is given in English.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Reading list and other learning resources

Course material will be provided by the teacher.