After successful completion of the course, students are able to understand a general practical overview of the different areas of information visualization, in particular in combination with data science methods, and apply it in implementation exercises.

In the course of this excercise, students will get to know different wide-spread and powerful visualization tools (e.g., d3) and useful data analysis tools (e.g., pandas, scikit-learn). Students will perform three smaller exercises with given data sets in groups: 

• Data preprocessing and visual inspection using Python
• Interactive coordinated views using d3, where a scaffold will be provided
• An extended visual data analysis using an environment of choice (e.g., Python notebook, R Shiny Dashboard, interactive webpage using d3). 

The exercises will be supported by multiple open labs and a TUWEL forum. Attendance of the accompanying lecture is recommended. 

The TUWEL course provides an overview of useful tools and libraries. 

See also Halls of Fames

• Solving programming tasks
• Presenting visual results of a data analysis task

ECTS Breakdown: 1,5 ECTS = 37,5 Stunden

• Programmieraufgabe: 30 Stunden
• Präsentation der Ergebnisse: 7,5 Stunden

Dates, links to open labs, instructions and submission links, as well as discussion forums can be found on TUWEL. 

Presentation and submission talk via Zoom (requires audio- and video connection via Zoom) or on-site.

programming experience; visualization or computer graphics knowledge advantageous