180.772 Seminar for Master Students in Data Science
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2022S, SE, 1.0h, 1.5EC
TUWEL

Properties

  • Semester hours: 1.0
  • Credits: 1.5
  • Type: SE Seminar
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to

  • desribe the problem tackled in their master thesis and its relevance
  • select an appropriate resarch method to tackle the problem
  • define and present a approriate approach to solve the problem
  • evaluate the approach with respect to the problem definition
  • present and defend the proposal as well as the results of the master thesis

Subject of course

This seminar is mandatory for all students of the Master Data Science.

Presentations of master thesis proposal and final results of the master thesis.

Teaching methods

  • Presentations on the status-quo of the master thesis.
  • Review of a proposal written by a colleague
  • Discussion on problem statement, methods, state-of-the-art, results and evaluation of the presented proposals / final master theses.

Mode of examination

Immanent

Additional information

When announcing each of the three seminar days, we will decide whether we go for a classroom session or run a Zoom session.

The registration of this course in TISS is optional. After the registration deadline, we add all registered students to the corresponding TUWEL course. All further announcements are made via the TUWEL course.

Please consider the plagiarism guidelines of TU Wien when writing your seminar paper: Directive concerning the handling of plagiarism (PDF)

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Mon08:30 - 15:0007.03.2022FAV Hörsaal 3 Zemanek (Seminarraum Zemanek) Preliminary Presentation + Seminar Day 1
Tue09:00 - 15:0003.05.2022FAV Hörsaal 3 Zemanek (Seminarraum Zemanek) Seminar Day 2
Thu08:00 - 15:0009.06.2022Seminarraum FAV EG C (Seminarraum Gödel) Seminar Day 3

Examination modalities

Assessment  of both presentations and of the review.

Course registration

Begin End Deregistration end
14.02.2022 00:01 04.03.2022 23:59

Curricula

Study CodeObligationSemesterPrecon.Info
066 645 Data Science Not specified

Literature

No lecture notes are available.

Language

English