252-3005-00L  Natural Language Understanding

SemesterSpring Semester 2020
Lecturersto be announced
Periodicityyearly recurring course
CourseDoes not take place this semester.
Language of instructionEnglish
CommentTakes place in HS20.



Courses

NumberTitleHoursLecturers
252-3005-00 VNatural Language Understanding
Does not take place this semester.
2 hrs
252-3005-00 UNatural Language Understanding
Does not take place this semester.
1 hrs
252-3005-00 ANatural Language Understanding
Does not take place this semester.
1 hrsto be announced

Catalogue data

AbstractThis course presents topics in natural language processing with an emphasis on modern techniques, primarily focusing on statistical and deep learning approaches. The course provides an overview of the primary areas of research in language processing as well as a detailed exploration of the models and techniques used both in research and in commercial natural language systems.
ObjectiveThe objective of the course is to learn the basic concepts in the statistical processing of natural languages. The course will be project-oriented so that the students can also gain hands-on experience with state-of-the-art tools and techniques.
ContentThis course presents an introduction to general topics and techniques used in natural language processing today, primarily focusing on statistical approaches. The course provides an overview of the primary areas of research in language processing as well as a detailed exploration of the models and techniques used both in research and in commercial natural language systems.
LiteratureLectures will make use of textbooks such as the one by Jurafsky and Martin where appropriate, but will also make use of original research and survey papers.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits5 credits
Examiners
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is only offered in the session after the course unit. Repetition only possible after re-enrolling.
Mode of examinationwritten 120 minutes
Additional information on mode of examinationGrade: 70% exam, 30% mandatory project.
Written aidsNone
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

 
Main linkInformation
LiteratureSPEECH and LANGUAGE PROCESSING - Jurafsky and Martin
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
CAS in Computer ScienceFocus Courses and ElectivesWInformation
DAS in Data ScienceMachine Learning and Artificial IntelligenceWInformation
Data Science MasterCore ElectivesWInformation
Computer Science MasterElective Focus Courses General StudiesWInformation
Computer Science MasterFocus Elective Courses Information SystemsWInformation
Computational Science and Engineering MasterElectivesWInformation