053631 LP Data Analysis Project (2022S)

12.00 ECTS (8.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik

Prüfungsimmanente Lehrveranstaltung

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Anmeldung von Mo 14.02.2022 09:00 bis Do 24.02.2022 10:00
Abmeldung bis Mo 14.03.2022 23:59

Details

max. 25 Teilnehmer*innen

Sprache: Englisch

Lehrende

Termine

In order to take part in the course, you have to register in u:space.
Then, we will need additional information to match you to an appropriate project. Once you have been assigned to a project, you will be accepted into the course.

We need a formal project application from you to match you to an appropriate project ***due 14. February***. You will find the corresponding form in Moodle at .

You need to email this completed form to info.datascience@univie.ac.at. Please use the subject line "2022S Application - {Your name}".

Only students who signed up for the class in univis/u:space are allowed to take the class. No exceptions possible.

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

In the course of a data analysis project, students acquire the ability to solve data science projects using the methods and techniques that the students have already learned during their studies. The range of possible project topics is quite broad, ranging from theoretical questions to applied topics with a potential industry partnership. Each project should be targeted at groups of 1-4 students, who will work on the project for the full semester, in addition to taking other classes. Each project will be supervised by our teaching staff, sometimes in cooperation with an industry partner. Common sessions and meetings will be arranged and agreed upon with the respective supervisor/s.

We are planning a joint "Data Science Day" at the beginning of summer semester 2022, in which the students present their work in a poster session to a broader audience including first and second semester students of the Data Science programs.

Art der Leistungskontrolle und erlaubte Hilfsmittel

The project must be completed by the end of the term.

Each project will consist of an implementation part (25%), documentation part (25%), presentation/poster part (25%), and participation part (25%) – to be specified by the particular project supervisor/s.

Mindestanforderungen und Beurteilungsmaßstab

The project must be completed by the end of the term. To pass, the average grade based on above examinations must be at least sufficient / 4.0.

Prüfungsstoff

To be determined by project supervisors.

Literatur