Digital Tools & Data Skills

Introduction & in-depth study

The participants:
• explain basic digital concepts, data structures and interfaces in energy and sustainability management..
• use common software tools for structured data collection and management.
• apply simple scripts to analyze, filter and graphically display data.
• analyze data sets for patterns, relationships and sources of error.
• reflect on the benefits, limits and ethical aspects of digital data processing in energy and sustainability management.

Scientific & Empirical Methods

- Introduction to digital tools and data management
- Introduction to programming and databases
- Data quality, error detection and cleansing
- Cloud and collaboration tools for data projects
- Data protection, data security and ethical aspects of data processing

- 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. (2025a). 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
- Runkler, T. A. (2025b). 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

Portfolio assessment

English

3

Lectures, discussions, case studies, group work

2