FI:PV173 NLP Seminar - Course Information
PV173 Natural Language Processing Seminar
Faculty of InformaticsSpring 2025
- Extent and Intensity
- 0/2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
In-person direct teaching - Teacher(s)
- doc. RNDr. Aleš Horák, Ph.D. (lecturer)
doc. Mgr. Pavel Rychlý, Ph.D. (lecturer)
RNDr. Zuzana Nevěřilová, Ph.D. (lecturer) - Guaranteed by
- doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Prerequisites
- Active work in the Laboratory of Natural language processing as well as an approval of registration by the lecturer (P.Rychly, A.Horak) is needed. The seminar is given in English. Presentations can be in English, Czech or Slovak.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 44 fields of study the course is directly associated with, display
- Course objectives
- The aim of the seminar is a presentation of results of student research (both doctoral and pregradual) in the NLP Laboratory (http://nlp.fi.muni.cz/).
- Learning outcomes
- After the seminar, the students will:
- gain insight into recent works in the field of computer natural language processing (NLP);
- be able to discuss NLP issues and solutions;
- understand an evaluation of NLP problems on the data sets used;
- design and present a custom solution for a selected NLP problem. - Syllabus
- The lectures consist mostly of students' presentations. The presentations and discussion are usually in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
- Literature
- Dan Jurafsky and James H. Martin. Speech and Language Processing (3rd ed. draft), 2024. https://web.stanford.edu/~jurafsky/slp3/
- Publications of NLP Centre
- NLP related works
- Teaching methods
- Students presentations, discussion.
- Assessment methods
- Students must attend the seminar regularly and present their own work. Credits are assigned to students according to the presented results.
- Language of instruction
- English
- Further Comments
- The course is taught each semester.
The course is taught: every week. - Teacher's information
- http://nlp.fi.muni.cz/en/NLPSeminar
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/fi/spring2025/PV173