The Faculty of Maritime Studies and Transport
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Transport Technology and Logistics

Information Science in Logistics


Core content includes: Knowledge of the importance, role and types of business information systems for logistics, types of information support for supply chains, information and intelligent systems supporting traffic, transportation and logistics, decision support tools and technologies, business intelligence tools and technologies, cloud computing - logistics cloud, Internet of Things concept, Big Data concept and Data Analytics. Digitization of logistics (digital logistics platforms, digital twins, blockchain technology in logistics). Artificial intelligence and machine learning in logistics.

In the exercises, students become familiar with the project management process, the use of various information and software systems, perform the specification of user requirements for software and create a simple data model. They learn some artificial intelligence techniques and machine learning algorithms.


Goals and competencies

Students will be familiar with the information tools and technologies used to efficiently carry out various logistics activities along the supply chain and will therefore be able to identify the basic characteristics, methods and examples of use, as well as the reasons for using a particular form of information systems or other IT tools developed for these purposes.

They learn how to create a specification of user requirements and a data model for the development of a particular logistics IS. Using a concrete example, they learn in detail the process of project management. They also learn about various techniques and algorithms of artificial intelligence and machine learning.

Basic literature