|Degree:||Master of Science (MSc)|
Data Science & Big Data
|University website:||Data Science|
The master’s programme in Data Science aims at providing a practically oriented and scientifically sound education in the field of modern data science. Data science is an essential driving force in today’s digital world. In almost all areas of the economy, large amounts of data are collected and generated. Recently, data-driven methods have also found their way into various parts of the natural sciences and humanities. The task of data science is to gain knowledge from ever bigger volumes of data, which represents added value for the respective area. This requires not only the development of efficient algorithms, but also a basic understanding of the interpretability and reliability of results. A diverse and interdisciplinary competence profile is required, which particularly includes the practical handling of large amounts of data, a solid mathematical and statistical foundation as well as knowledge in the respective area of application. In addition, the rapid developments in data science raise ethical and legal questions. The master’s programme in Data Science at the University of Vienna extensively reflects all these core competencies and puts an emphasis on the interdisciplinary and heterogeneous character of Data Science, which is ensured by means of a specialisation in individual areas.
The study programme consists of the compulsory module groups
In the module “Specialisation”, students can specialise in individual areas due to the multifaceted range of courses offered, e.g. in principles of Mathematics, Computer Science and Statistics or in various fields of application ranging from the Natural Sciences to Economics and from the Social Sciences to the Humanities. In order to complete the degree programme, students have to write a master’s thesis and pass a master’s examination.
Graduates receive a sound and broad education in core modules, including algorithmic, mathematical and statistical foundations, the handling of large amounts of data as well as explorative data analysis. Additionally, graduates are familiarised with ethical and legal aspects.
They gain in-depth knowledge in concrete fields of application, e.g. from humanities, language processing, finance, medicine, physics, or computational science.
Thereby, they acquire the basis for a doctoral or PhD programme in Mathematics, Computer Science or Statistics/OR and practical skills which are in great demand on the labour market. For example, graduates are qualified to deal with huge volumes of data, statistically analyse complex data and develop, implement and analyse efficient algorithms for data analysis.