822048 :Data Visualization (CSAI/HAIT/NMD/BDM/T&C)

General info

Instruction language English
Type of Instruction We are Our Brains; From the Womb to Alzheimer's (Lecture schedule)
Type of exams paper (No data available yet)
Course load:6 ECTS credits
Registration:Enrollment via Blackboard before start of lectures
Blackboard InfoLink to Blackboard (When you see 'Guest are not allowed in this course', please login at Blackboard itself)


dr.ing. S.C.J. Bakkes (coordinator)


At the end of the course, students will be able to:
- recognize and provide insight into patterns in data,
- design and implement 2D data visualizations,
- critically reflect on data visualizations,
- give data-driven presentations.


Data visualization concerns the presentation of data in a visual format (e.g., in a pictoral or graphical format). It enables decision makers to (1) comprehend information quickly, (2) identify relationships and patterns, (3) pinpoint emerging trends, and (4) communication the story to others.

Given the current trend of a growing volume and variety of data streams, it is important that not only a human designer can create appropriate data visualizations, but that the process can be automated to assist the human interpreter. As such, the present course is particularly focused on how effective data visualizations can be generated automatically, building upon established methods for data visualization and on existing toolkits.


The course consists of a large group project (60% of the final grade) and individual assignments (40% of the final grade). The project is driven by structured group discussions, presentations (both expert + student), critical reflections, combined with team-based practical implementation of the ideas on the basis of existing tools. The individual assignments concern the critical reflection on data visualizations, and the implementation of a data visualization.

The course is somewhat technical in nature. As such, basic programming skills are a plus (but are not required).

Compulsory Reading

  1. On-line articles and slides on Blackboard.

Recommended Prerequisites

Basic programming skills are a plus (but are not required)

Required Prerequisites


Compulsory for

  • Bachelor CIW: Cognitive Science and Artificial Intelligence ( 2017 )

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