Data Science & Intelligent Analytics PT
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Visual Analytics for Data Science

level of course unit

Master course

Learning outcomes of course unit

Graduates have basic knowledge of data visualization and visual communication. They can independently develop visualizations and use these for communication purposes. Graduates can work with various illustration tools and illustration libraries in order to depict data and analysis results in a meaningful manner. They also know how to use visual analytics in order to test hypotheses and access data.

prerequisites and co-requisites

not specified

course contents

Students learn how to deal with various illustration tools and illustration libraries. They also learn about the fundamentals of visual communication and visual analytics.

The course content specifically encompasses these topics:
-Evaluation tools with visual orientation, e.g. BI tools such as MS PowerBI, tableua, QlikView
-Illustration libraries, e.g. matplotlib.pyplot, gglot2
-Rules for visual communication, e.g. Hichert SUCCESSS

recommended or required reading

- Chang, W. (2013) R Graphics Cookbook: Practical Recipes for Visualizing Data. 1. Auflage, O´Reilly, Farnham (ISBN: 978-1449316952).
- Chen, C.; Härdle, W. K.; Unwin, A. (2008) Handbook of Data Visualization. 1. Auflage, Springer, Berlin (ISBN: 978-3-662-50074-3).
- Dale, K. (2016) Data Visualization with Python and Javascript: Scrape, Clean, Explore & Transform Your Data. 1. Auflage, O´Reilly, Farnham (ISBN: 978-1491920510).
- Murray, S. (2017) Interactive Data Visualization for the Web: An Introduction to Designing with D3. 2. Auflage, O´Reilly, Farnham (ISBN: 978-1491921289).
- Rahlf, T. (2017) Data Visualisation with R: 100 Examples. 1. Auflage, Springer, Wiesbaden (ISBN: 978-3319497501).

assessment methods and criteria

Final examination

language of instruction

German

number of ECTS credits allocated

3

planned learning activities and teaching methods

-Lecture with discussion
-Interactive workshop
-Case studies

semester/trimester when the course unit is delivered

3

name of lecturer(s)

Head of studies

year of study

2

recommended optional program components

N.A.

course unit code

DPR.7

type of course unit

ILV

mode of delivery

In-course class

work placement(s)

N.A.