Data Science im Supply Chain Management (SCM-M-06)
Type: lecture/practical seminar
Type of examination: written exam, 60 min.
ECTS: 6
Cycle: winter term
Lecturer
Christian Menden
Requirements
Basics of ecometrics
Content
Embedded in the theoretical context of supply chain management, the course deals with the basics and methods from the field of data science and analytics. At the end of the course, students should be able to work independently on a small data science project in the area of supply chain management. In doing so, they will go through all steps of the data science pipeline and implement the project practically using R or Python.
Essential learning content:
- Introduction into the basics of data science and analytics in the context of supply chain management
- Consideration of relevant methods, particularly from the fields of artificial intelligence and machine learning
- Comprehensive explanation of the entire data science pipeline from the definition of a use case to data import, data visualization, data cleansing, the application of various analysis methods to the development of user interfaces and the deployment of corresponding solutions on a cloud infrastructure
- Treatment of different application examples from the field of the supply chain management (e.g. demand forecast, price forecast)
- Elaboration of a case study by using data science and analytics methods
- Guest lecture from practice; the respective topic will be announced in the lecture
Note
This information is indicative only and subject to change.
Legally binding information on legal aspects of examinations is only provided by the Examination Board.