252-0945-05L  Doctoral Seminar Machine Learning (HS17)

SemesterAutumn Semester 2017
LecturersJ. M. Buhmann, T. Hofmann, A. Krause, G. Rätsch
Periodicityevery semester recurring course
Language of instructionEnglish
CommentOnly for Computer Science Ph.D. students.



Catalogue data

AbstractAn essential aspect of any research project is dissemination of the findings arising from the study. Here we focus on oral communication, which includes: appropriate selection of material, preparation of the visual aids (slides and/or posters), and presentation skills.
ObjectiveThe seminar participants should learn how to prepare and deliver scientific talks as well as to deal with technical questions. Participants are also expected to actively contribute to discussions during presentations by others, thus learning and practicing critical thinking skills.
Prerequisites / NoticeThis doctoral seminar of the Machine Learning Laboratory of ETH is intended for PhD students who work on a machine learning project, i.e., for the PhD students of the ML lab.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits1 credit
ExaminersJ. M. Buhmann, T. Hofmann, A. Krause
Typeungraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Courses

NumberTitleHoursLecturers
252-0945-00 SDoctoral Seminar Machine Learning2 hrs
Tue12-13CAB G 56 »
J. M. Buhmann, T. Hofmann, A. Krause, G. Rätsch

Groups

No information on groups available.

Restrictions

PriorityRegistration for the course unit is only possible for the primary target group
Primary target groupDoctorate Computer Science (264002)

Offered in

ProgrammeSectionType
Doctoral Department of Computer ScienceDoctoral and Post-Doctoral CoursesWInformation