ÖH WU > Service > Aktuelle Studien-Infos > Data Science
Aktuelle Studien-Infos

Data Science

Spezialisierung: BW, IBW, WINF, WiRe, BBE              Komplementärfach: VW, WUPOL

Duration: in 2 semester doable

Admission: Greencard, entry exam, grade transcript

Spots per semester: 60

aktualisiert am 02.08.2023
Teilen via


The efficient processing and analysis of ever increasing amounts of data ("Big Data") is becoming more and more important. With the introduction of Special Business Administration, this hot topic is taken up.

The fundamentals of information processing, statistics and analysis as well as law are taught. Within the framework of project work, you will learn how to process and analyze data using innovative applications. 



1.     With applying to the course "Access to Specialization: Data Science" you consent to us requesting from the vice rectorate of teaching your grades transcript (Sammelzeugnis). 

2.     The course "Access to Specialization: Data Science" consists of two Tutorial sessions (attendance voluntary) and an obligatory (for all, even for a green card or with excellent average grades) entry exam, which will be held as an online-exam

3.     Places in the SBWL (overall at maximum 60) will be assigned as follows:

a.     10 spots are reserved for the top overall average grades, where in case of ties we take the average of the GreenCard courses as ranking/tie breaker

b.     A maximum of 10 further spots are reserved to students qualified for a GreenCard; in case of more GreenCard qualified applicants, the overall average grade we take the average grade as ranking/tie breaker

c.     The remaining spots are filled by the results of the entry exam, where again the overall average grades will be used as a tie breaker in case of ties


Students who completed all of the following courses and achieved an average grade of 1,5 or lower across the three courses:

    • Grundzüge der Programmierung/Algorithmisches Denken und Programmierung
    • Datenbanksysteme/Data Knowledge Engineering
    • Einführung in die Statistik
  •  BBE
    • Quantitative Methods 1
    • Quantitative Methods 2
    • Business Analytics 2

are automatically qualified for the SBWL, but should nevertheless complete the entry exam, since it will serve as the first partial assessment for the SBWL course “Data Processing 1”

Students who want to make use of this “Greencard-Option” should send a confirmation (Sammelzeugnis) of the necessary grades in advance to data-science@ai.wu.ac.at with the subjectline “Greencard SBWL Data Science"



1.     Semester

  • Course 1 – Data Processing 1
  • Course 2 – Data Analytics
  • Course 3 – Data Processing 2: Scalable data processing, legal & ethical foundations of data science

2.     Semester

  • Course 4 – Applications of Data Science
  • Course 5 – Data Science Lab


Bachelor Thesis

 Any of the institutes part-taking in this SBWL offer related bachelor thesis topics around "Data Science”. For instance, the Institute of Data, Process, and Knowledge Management offers its BSc and MSc topics each semester on this Web page: https://www.wu.ac.at/en/dpkm/write-a-thesis/ where you also find details about the prerequisites, application process and timeline for theses offered by the institute. The final "Data Science Lab” in the SBWL, where you work on bigger Data Science projects also offers excellent opportunities for follow-up topics that could be elaborated in a BsC thesis.


Career Profils

In a famous article, "Data Scientist" was branded the "sexiest job of the 21st" century... However, the roles and jobs that require data science skills have diversified, ranging from Data Scientists for humans (who develop data products or tell stories using data, such as in Data Journalism), to Data Scientists for machines, who run and manage the big "machine rooms" behind large data-driven businesses, with roles ranging from very technical ones, to "Data Stuarts" who manage data at a department level, up to C-level positions (such as "Chief Data Officer" or "Chief Digital Officer"), but also - as the name implies - scientific roles in academia or industry research. With this SBWL - as for any university education - you will maybe not directly qualify for a particular job, but you will build up an important puzzle piece of knowledge and experience valuable if you're interested in such careers.



Eine der wenigen SBWLs, in der nicht nur heiße Luft gelehrt, sondern sehr viel Wert auf Praxisnähme und vor allem Praxisrelevanz gelegt wird. Gleichzeitig ist der Workload durchaus vertretebar (also nicht so furchtbar wie bspw. E&I), selbst dann wenn man davon keine Berührungspunkte mit Programmieren etc. hatte. Für mich eindeutig die spannendste und bei Weitem beste SBWL an der WU!

aktualisiert am 02.08.2023
Teilen via