Data Visualization & Visual Analytics
Niveau
Master's degree program
Learning outcomes of the courses/module
The participants:
• can describe data visualization as well as visual communication
• can independently develop visualizations and use them for communication purposes
• can work with various visualization tools and libraries to present data and analysis results in a meaningful way
• can describe data visualization as well as visual communication
• can independently develop visualizations and use them for communication purposes
• can work with various visualization tools and libraries to present data and analysis results in a meaningful way
Prerequisites for the course
No prerequisites
Course content
The following topics are covered in the course:
- Analysis tools with a visual focus, e.g., BI tools such as MS Power BI, Tableau, QlikView
- Visualization libraries, e.g., matplotlib.pyplot, ggplot2
- Principles of visual communication, e.g., Hichert SUCCESS
- Analysis tools with a visual focus, e.g., BI tools such as MS Power BI, Tableau, QlikView
- Visualization libraries, e.g., matplotlib.pyplot, ggplot2
- Principles of visual communication, e.g., Hichert SUCCESS
Recommended specialist literature
- Wilke, C. O. (2019): Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures, O'Reilly
- Knaflic, C. N.; Kauschke, M. (2017): Storytelling mit Daten: Die Grundlagen der effektiven Kommunikation und Visualisierung mit Daten, Vahlen
- Knaflic, C. N.; Kauschke, M. (2017): Storytelling mit Daten: Die Grundlagen der effektiven Kommunikation und Visualisierung mit Daten, Vahlen
Assessment methods and criteria
Written exam or seminar paper
Language
English
Number of ECTS credits awarded
4
Semester hours per week
Planned teaching and learning method
The following methods are used:
- Lecture with discussion
- Interactive workshop
- Case studies
- Lecture with discussion
- Interactive workshop
- Case studies
Semester/trimester in which the course/module is offered
3