186.143 Information Visualization
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023S, UE, 1.0h, 1.5EC


  • Semester hours: 1.0
  • Credits: 1.5
  • Type: UE Exercise
  • Format: Hybrid

Learning outcomes

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.

Subject of course

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., pandasscikit-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

 The exercises will be presented in the first lecture unit of Information Visualization VO


Teaching methods

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

Mode of examination


Additional information

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. 



Examination modalities

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

Course registration

Begin End Deregistration end
08.02.2023 00:00 29.03.2023 23:59 29.03.2023 23:59


Study CodeObligationSemesterPrecon.Info
066 645 Data Science Not specified
066 926 Business Informatics Mandatory elective
066 932 Visual Computing Mandatory elective
066 933 Information & Knowledge Management Mandatory elective


No lecture notes are available.

Previous knowledge

programming experience; visualization or computer graphics knowledge advantageous

Accompanying courses