The remarkable increase in the volume and complexity of available data – and the new technology that has been developed to process it – requires a combined multi-disciplinary approach to design an overall strategy to transform data into useful information. Key ingredients for developing a successful strategy include data manipulation and visualization, large-scale computing, statistical modelling, learning techniques and algorithmic thinking. This Masters programme provides a solid and modern preparation, allowing graduates to understand and manage the many aspects of carrying out a complete data analysis, including its acquisition, management, and statistical analysis.
ALGORITHMIC METHODEN DER DATA – MINING UND LABOR;
FUNDAMENTALS OF DATA SCIENCE AND LABORATORY;
STATISTICAL METHODS IN DATA SCIENCE AND LABORATORY;
INTELLECTUAL PROPERTY COMPETITION AND DATA PROTECTION LAW;
NETWORKING FOR BIG DATA AND LABORATORY;
STATISTICAL METHODS IN DATA SCIENCE AND LABORATORY 1;
DATA MANAGEMENT FOR DATA SCIENCE;
CLOUD COMPUTING;
DATA MINING TECHNOLOGY FOR BUSINESS AND SOCIETY;
DATA MONITORING ANALYSIS AND COMMUNICATION;
STATISTICAL LEARNING;
QUANTITATIVE MODELS FOR ECONOMIC ANALYSIS AND MANAGEMENT;
DATA PRIVACY AND SECURITY;
SOCIAL AND BEHAVIORAL NETWORKS;
SIGNAL PROCESSING FOR BIG DATA;
NETWORK INFRASTRUCTURES;
OPTIMIZATION METHODS FOR MACHINE LEARNING;
STATISTICAL METHODS FOR OFFICIAL STATISTICS;
BIOINFORMATICS;
PROBABILITY AND STOCHASTIC PROCESSES FOR DATA SCIENCE;
DIGITAL EPIDEMIOLOGY;
EARTH OBSERVATION DATA ANALYSIS;
ECONOMICS OF INFORMATION;
EFFICIENCY AND PRODUCTIVITY ANALYSIS;