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Applied Supply Chain Analytics - From Data to Decisions (Bachelor Logistics, Module MB-296, 5 ECTS)

Enrollment in Moodle possible from today! Link and registration key see below!

The lecture "Applied Supply Chain Analytics - From data to decisions" gives an overview of modern methods for data processing in supply chains in its entirety, i.e. from the acquisition of raw data, its integration and analysis to automated decision-making. The aim of the event is to convey the basic ideas of important methods and to facilitate the students' access to important IT tools in practical units.

For this purpose, the following content is addressed using examples from supply chain management:

  • Introduction to the basics of programming Python (Pyhton Crashcourse) as well as accompanying the lecture the introduction of important Python libraries from the area of ​​data analytics (e.g. pandas, requests, seaborn, folium, scikit-learn)
  • First overview of methods and technologies for data acquisition, data integration and data storage as well as typical data sources, data types and data formats in logistics
  • Introduction of possibilities for exploratory analysis and visualization of supply chain data
  • Introduction of basic concepts for selected methods for data analysis (descriptive / predictive analytics) from the areas of statistics and machine learning based on typical questions from supply chain management and logistics

The exercise accompanying the lecture is integrated into the lecture like a case study in the form of "Supply Chain Analytics Challenges". Methods are deepened on the basis of application examples with real data from practice. The tasks are implemented in group work, results are interpreted and presented.

Prior knowledge of statistics is recommended for participation in the event.

The language of the event is English. In order to be able to take part in the oral examination, the processing of the Analytics Challenges is a prerequisite (see also section Examination).