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Enhancing Digitalization Through Machine Learning

Machine learning in theory and practice – what reads so excitingly and is abbreviated to MaLiTuP has great potential for harnessing data. MaLiTuP is a qualification measure developed by the Fraunhofer CML, the Institute for Maritime Logistics and the Institute for Software Systems, both at the TU Hamburg. MaLiTuP is funded by the German Federal Ministry of Education and Research and is aimed at both students and professionals. MaLiTuP aims at the use of increased data analysis in logistics.
Many companies collect and store large amounts of data, such as transport routes and

transshipment processes, but they are often only evaluated in part. MaLiTuP is intended to qualify the participants to analyse these data sets and to create and implement concepts for their evaluation. It quickly becomes clear that the same set of data can often contain many different insights. Thus, historical AIS data from ocean shipping are not only used to determine travel times from A to B under various conditions, but also ideal routes or manoeuvres during encounters or overtaking.

Three qualification levels are to be implemented by the end of the project: a basic level, which includes an introductory lecture (incl. practical exercise), an advanced level, in which project work on practical tasks is carried out, and a professional level, in which practitioners from companies receive certified training.

The first results of MaLiTuP were presented at the Hamburg Inter- national Conference of Logistics (HICL).
For further practical work, tasks from the real world are sought.

A good opportunity for logistics companies to have their own data treasures evaluated individually or to develop ideas for meaningful analyses with project partners.
Source: CML Fraunhofer

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