053631 LP Data Analysis Project (2024S)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 12.02.2024 09:00 bis Do 22.02.2024 09:00
- Abmeldung bis Do 14.03.2024 23:59
Details
max. 25 Teilnehmer*innen
Sprache: Englisch
Lehrende
- Torsten Möller
- Tara Andrews
- Jan Fabian Ehmke
- Steffen Elting
- Rico Kötschau
- Sebastian Ratzenböck
- Benjamin Roth
- Anastasiia Sedova
Termine (iCal) - nächster Termin ist mit N markiert
Montag
04.03.
16:45 - 18:15
Hörsaal 3, Währinger Straße 29 3.OG
(Vorbesprechung)
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
During a data analysis project, students acquire the ability to solve data science projects using the methods and techniques they 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. Most projects are for single students, with the intention that they will transform into suitable thesis projects. At times, projects can be group projects for 2-3 students, who will work on the project together.We are planning a joint "Data Science Day" at the beginning of the summer semester 2025, 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 (22,5%), documentation part (22,5%), presentation/poster part (22,5%), and participation part (22,5%) – to be specified by the particular project supervisor/s. In addition, we will ask you to broaden your horizons by attending a couple of research talks organized by the research network during the semester (10%).
Mindestanforderungen und Beurteilungsmaßstab
The project must be completed by the end of the term. The grading scale for the course will be:
1: at least 87.5%
2: at least 75.0%
3: at least 62.5%
4: at least 50.0%
1: at least 87.5%
2: at least 75.0%
3: at least 62.5%
4: at least 50.0%
Prüfungsstoff
To be determined by project supervisors.
Literatur
To be determined by project supervisors.
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mo 25.03.2024 15:25