Datenanalyse und Wissensrepräsentation in der Produktion und Logistik

This module covers the fundamentals of data analysis in manufacturing and logistics companies. The course covers the entire knowledge discovery process, from data storage in relational structures or NoSQL databases through selected data mining and artificial intelligence methods to knowledge representation techniques such as semantic networks. The various influencing factors and constraints for knowledge discovery are explained using selected procedural models, and their application to current industry challenges is discussed. In the section on specific fundamentals, methods from the fields of cluster analysis, decision trees, and nearest-neighbor classification are introduced. In addition, related practical areas such as text mining, large language models, and data migration are discussed. The seminar is designed to be practice-oriented and, in addition to interactive discussions on selected topics from the course, covers a basic introduction to the Unified Modeling Language (UML) modeling technique as well as activity network diagram techniques in IT projects.