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[ 921CDASI17 ] Studienfach Data Science (CS)

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Workload Form der Prüfung Ausbildungslevel Studienfachbereich VerantwortlicheR Anbietende Uni
0-27 ECTS Gliederung M - Master Informatik Ulrich Bodenhofer Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Masterstudium Computer Science 2017W
Ziele Recent advances in data analytics along with rapidly growing amounts of data allow for completely new opportunities to solve hard real-world problems in a data-driven manner. This is impressively demonstrated by the latest achievements in, e.g., genome analysis, image recognition in self-driving cars, or situation detection in crisis events. Data science is an interdisciplinary field at the interface between computer science and statistics dealing with huge amounts of multivariate, heterogeneous data, which gets analyzed and interpreted in order to draw adequate decisions. The specialization in Data Science aims at providing an understanding of fundamental technologies such as, machine learning, pattern recognition, data mining, data visualization and big data management, both from a computer science and statistics perspective, and accompanies them by the necessary background in database and software technologies. Data scientists are highly demanded in industry across various domains, such as, medicine, smart production, finance and marketing.
Lehrinhalte The contents of this subject result from the contents of its courses.
Untergeordnete Studienfächer, Module und Lehrveranstaltungen