Inhalt

[ 921DASI17 ] Subject Data Science

Versionsauswahl
Workload Mode of examination Education level Study areas Responsible person Coordinating university
37,5 ECTS Accumulative subject examination M - Master's programme Computer Science Ulrich Bodenhofer Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computer Science 2017W
Objectives 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.
Subject The contents of this subject result from the contents of its courses.
Subordinated subjects, modules and lectures