252-3005-00L  Natural Language Understanding

SemesterSpring Semester 2019
LecturersM. Ciaramita, T. Hofmann
Periodicityyearly recurring course
Language of instructionEnglish
CommentNumber of participants limited to 200.



Courses

NumberTitleHoursLecturers
252-3005-00 VNatural Language Understanding2 hrs
Mon10:15-12:00CAB G 11 »
M. Ciaramita, T. Hofmann
252-3005-00 UNatural Language Understanding1 hrs
Mon13:15-14:00HG E 5 »
M. Ciaramita, T. Hofmann

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.
Learning 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 credits4 credits
ExaminersM. Ciaramita, T. Hofmann
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

Places200 at the most
Waiting listuntil 03.03.2019

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