Visualization
(in German: Visualization )
Module-ID: FIN-INF-102812 |
| Link: | LSF |
| Responsibility: | Bernhard Preim |
| Lecturer: | Bernhard Preim |
| Classes: |
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| Applicability in curriculum: | - M.Sc. DKE: Applied Data Science - M.Sc. DE: Methoden der Informatik - M.Sc. VC: Visual Computing |
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Abbreviation VIS |
Credit Points 6 |
Semester Winter |
Term ab 1. |
Duration 1 Semester |
Language english |
Level Master |
Intended learning outcomes:
Students ...
- understand how physiological perception affects visualization effectiveness
- know basic visualization techniques
- can generate appropriate visualizations for business and statistical data
- obtain a dataset with at least 100 observations and 5 attributes, formulate two analytical questions, and create data visualizations to answer these questions.
Content:
- Visualization goals and quality criteria
- Understanding of fundamentals of visual perception
- Overview of data structures in visualization
- Basic algorithms (Isolines, color scales, diagram techniques),
- Direct and indirect visualization of volume data
- map-based visualization
- dashboard design
- Information visualization
Workload:
56h contact time + 124h self study
| Pre-examination requirements: | Type of examination: | Teaching method / lecture hours per week (SWS): |
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Written exam |
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| Prerequisites according to examination regulations: | Recommended prerequisites: |
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none |
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| Media: | Literature: |
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