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Projects & Cooperations / ÜberDax:


The progressive digitalization of economy and society is making more and more processes observable and thus open to partial automation or at least decision support through machine learning models: in Industry 4.0 machine data can be used used to detect problems early and avoid failures or to reduce manufacturing variances and make planning more robust, in autonomous driving cars sensor and video data is already in use for simple maneuvers such as parking and will soon also be used for driving on highways, in the area of ​​e-health they help in segmenting organs and tumors or predicting how a tumor will most likely develop.

As part of the Master program "International Master in Data Analytics" at the University of Hildesheim, in close cooperation with SMEs and industrial companies, students learn to analyze problems with complex data, the design of suitable machine learning models and associated learning algorithms at the level of current research. For this purpose, a Complex Data Lab will be set up, in which the students will first use clear examples to systematically familiarize the various data modalities and their characteristics. In student research projects, these skills are tested on relevant examples with complex data.

Geldgeber: BMBF


Lars Schmidt-Thieme
Ahmed Rashed