Digitization in Energy & Sustainability Management

Consolidation

The students are able to:
• Describe contents, results/applications and working methods of Data Science
• Apply basic functions in the processing of mass data including evaluation functions
• Describe basic concepts of programs for evaluating large quantities of data and independently create simple program codes for evaluations
- Apply tools for the evaluation of data

Scientific and Empirical Methods (WIS.1)

• Basic programming knowledge for data preparation
• Analysis and presentation of information from data sets

• Amos, D., Bader, D., Jablonski, J., & Heisler, F. (2021). Python basics: A practical introduction to Python 3 (Revised and updated 4th edition). Real Python.
• Matthes, E. (2023). Python crash course: A hands-on, project-based introduction to programming (3rd edition). No Starch Press.
• Runkler, T. A. (2025). Data Analytics: Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction (4th ed. 2025). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-45951-2

Examination and portfolio

English

4

Blended Learning

2