Universität Wien FIND

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Further information about on-site teaching can be found at https://studieren.univie.ac.at/en/info.

052320 VU Advanced Topics in Data Analysis (2018S)

Continuous assessment of course work

Registration/Deregistration

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

There will be no lecture at the 23rd of May 2018.
The lecture from Wednesday, 6th June 2018 is postponed to Friday, 8th of June 2018 at 14:30. The lecture will take place in the seminarroom 2, in the basement.

Wednesday 07.03. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 14.03. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 21.03. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 11.04. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 18.04. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 25.04. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 02.05. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 09.05. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 16.05. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 23.05. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 30.05. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 06.06. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Friday 08.06. 14:00 - 18:15 Seminarraum 2, Währinger Straße 29 1.UG
Wednesday 13.06. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 20.06. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG
Wednesday 27.06. 13:15 - 16:30 PC-Unterrichtsraum 6, Währinger Straße 29 2.OG

Information

Aims, contents and method of the course

In this course will cover current topics in data mining reseach.

Goals: Participants are able to perform independent literature research, decide which techniques to apply to practical problems, perform a complete data mining process including all stages.

Contents: Current conference tutorials on "hot topics" of data mining research, e.g. on information-theoretic data mining, high-performance data mining, mining time series and graphs, research papers on these topics and participation in a data mining contest.
Methods: Lecture, student presentations, guided group work on practical challenges.

Assessment and permitted materials

Two practical tasks:

- 20% reviewing and presentation of a research paper
- 60%: participation in a data mining contest in programming groups
- 20%: active participation in the lecture

Besides the material provided in the course and elaborated by the participants by doing literature research and group work, no further auxilliary material is allowed (also not required).

Minimum requirements and assessment criteria

The grading scale for the course will be:
>87,00 % 1
between 75,00 % and 86,99 %: 2
between 63,00 % and 74,99 %: 3
between 50,00 % and 62,99 %: 4
< 50% : 5

Attendence in the lectures is mandatory.

Examination topics

Slides, research papers, independent literature study

Reading list

Lecture slides, research papers.

Association in the course directory

Module: AT-DA

Last modified: Mo 07.09.2020 15:30