2205 Interdisziplinäres Forschungsseminar: Doing Data Science
Univ.Prof. Dr. Nadia Abou Nabout, Univ.Prof. Dr. Kurt Hornik, Univ.Prof. Dr. Axel Polleres
  • LV-Typ
  • Semesterstunden
  • Unterrichtssprache
01.09.2015 bis 01.11.2015
Anmeldung über LPIS
Hinweise zur LV
Planpunkt(e) Doktorat/PhD
Wochentag Datum Uhrzeit Raum
Mittwoch 09.12.2015 13:30 - 17:30 EA.6.026
Dienstag 15.12.2015 12:00 - 14:00 D3.0.233
Dienstag 15.12.2015 14:00 - 16:00 TC.2.01
Donnerstag 28.01.2016 14:00 - 18:00 TC.3.05

Inhalte der LV

This course covers presentation and discussion of topics related to data science. Students are expected to work together in interdisciplinary teams and search for suitable data sets they would like to analyze during the course. Specific topics are determined in the first session and will reflect the specific needs of participants. In addition, students are expected to present chapters of the book "Doing Data Science" ( 

Lernergebnisse (Learning Outcomes)

This course focuses on research applying data science techniques.

Upon completion of the course participants will be able to:

  1. define a research problem that is novel, non-trivial to solve;
  2. solve the research problem using large amounts of data by applying data science methods;
  3. present results at scientific conferences. 


The course uses a combination of student presentations of group projects and book chapters ("Doing Data Science"), work in interdisciplinary teams, and joint discussion and review of journal articles relevant for data science. 

Leistung(en) für eine Beurteilung

  1. Preparation and active participation (30%): Assessment of participation in class and preparation in terms of reading preparatory materials;
  2. Presentation (50%): Quality of own presentations with regard to scientificquality and presentation skills;
  3. Reviewing others' contributions (20%): Quality of contribution in reviewingother teams' scientific work.

Teilnahmevoraussetzung(en) und Vergabe von Wartelistenplätzen

  • Admission to doctoral or PhD program
  • Topical fit (if in doubt, please contact one of the instructors)


1 Autor/in: Cathy O'Neil, Rachel Schutt
Titel: Doing Data Science: Straight Talk from the Frontline

Verlag: O'Reilly Media
Auflage: 1
Jahr: 2013
Prüfungsstoff: Ja
Diplomprüfungsstoff: Nein
Empfehlung: Unbedingt notwendige Studienliteratur für alle Studierenden
Art: Buch

Erreichbarkeit des/der Vortragenden

Prof. Dr. Nadia Abou Nabout;; +43 1 31336 4900

Additional (blank) field

Invitiations are being sent prior to each session.
Zuletzt bearbeitet: 30.08.2015