136014 UE Data Visualization in the Digital Humanities (2021W)
Continuous assessment of course work
Labels
REMOTE
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from We 01.09.2021 09:00 to We 29.09.2021 23:59
- Deregistration possible until Su 31.10.2021 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
The course will be held online.
Course dates:15.10.2021, 14:00-19:0019.11.2021, 14:00-19:00
17.12.2021, 14:00-19:00
21.01.2022, 14:00-19:00
- Friday 15.10. 14:00 - 19:00 Digital
- Friday 19.11. 14:00 - 19:00 Digital
- Friday 17.12. 14:00 - 19:00 Digital
- Friday 21.01. 14:00 - 19:00 Digital
Information
Aims, contents and method of the course
Assessment and permitted materials
• Regular homework assignments: 4 x 20 points
• In-class participation: 20 points
• In-class participation: 20 points
Minimum requirements and assessment criteria
In this course, we will work with the programming language R, which is a versatile tool for data visualization and analysis. No preliminary knowledge of R is required, but having some experience in any programming language will certainly be beneficial.The grading scale for the course will be:90-100 points: sehr gut
80-89 points: gut
70-79 points: befriedigend
60-69 points: genügend
0-59 points: nicht genügend
80-89 points: gut
70-79 points: befriedigend
60-69 points: genügend
0-59 points: nicht genügend
Examination topics
Completion of in-class assignments and homework assignments, active contribution to discussions in class.
Reading list
To be announced in class.
Association in the course directory
DH-S II
S-DH (Cluster III: Theater, Film und Medien)
S-DH (Cluster III: Theater, Film und Medien)
Last modified: Th 04.07.2024 00:13
• basic principles of human visual perception and processing.
• basic theoretical concepts of how to design informative and reader-friendly visualizations.
• various types of static and interactive visualizations, such as bar charts, point, line and violin plots, heat maps, word clouds, maps, networks, trees, or timelines.
• the programming language R and relevant R packages for data visualization.Students will do plenty of hands-on exercises in R, in which they will practice creating different types of data visualizations.