101-0522-10L  Doctoral Seminar Data Science and Machine Learning in Civil, Env. and Geospatial Engineering

SemesterSpring Semester 2021
LecturersB. Soja, E. Chatzi, F. Corman, O. Fink, I. Hajnsek, M. A. Kraus, M. Lukovic, K. Schindler, M. J. Van Strien
Periodicityevery semester recurring course
Language of instructionEnglish
CommentNumber of participants limited to 21.



Courses

NumberTitleHoursLecturers
101-0522-10 SDoctoral Seminar Data Science and Machine Learning in Civil, Env. and Geospatial Engineering Special students and auditors need a special permission from the lecturers.
Remark: No course on 07.04.2021 (ETH Easter break).
The lecturers will communicate the exact lesson times of ONLINE courses.
2 hrs
Wed/114-16ON LI NE »
B. Soja, E. Chatzi, F. Corman, O. Fink, I. Hajnsek, M. A. Kraus, M. Lukovic, K. Schindler, M. J. Van Strien

Catalogue data

AbstractCurrent research in machine learning and data science within the research fields of the department. The goal is to learn about current research projects at our department, to strengthen our expertise and collaboration with respect to data-driven models and methods, to provide a platform where research challenges can be discussed, and also to practice scientific presentations.
Objective- learn about discipline-specific methods and applications of data science in neighbouring fields
- network people and methodological expertise across disciplines
- establish links and discuss connections, common challenges and disciplinespecific differences
- practice presentation and discussion of technical content to a broader, less specialised scientific audience
ContentCurrent research at D-BAUG will be presented and discussed.
Prerequisites / NoticeThis doctoral seminar is intended for doctoral students affiliated with the Department of Civil, Environmental and Geomatic Engineering. Other students who work on related topics need approval by at least one of the organisers to register for the seminar.

Participants are expected to possess elementary skills in statistics, data
science and machine learning, including both theory and practical modelling and implementation. The seminar targets students who are actively working on related research projects.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits1 credit
ExaminersB. Soja, E. Chatzi, F. Corman, O. Fink, I. Hajnsek, M. A. Kraus, M. Lukovic, K. Schindler, M. J. Van Strien
Typeungraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.
Additional information on mode of examinationUngraded semester performance. Presence is mandatory to pass the
seminar. Every participant has to present his/her reseach.

Learning materials

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

Groups

No information on groups available.

Restrictions

General : Special students and auditors need a special permission from the lecturers
Places21 at the most
PriorityRegistration for the course unit is only possible for the primary target group
Primary target groupDoctorate Civil Engineering (114102)
Doctorate Environmental Engineering (114202)
Doctorate Geomatic Engineering (114302)
Waiting listuntil 17.02.2021

Offered in

ProgrammeSectionType
Doctoral Department of Civil, Environmental and Geomatic EngineeringAdditional CoursesWInformation