Kies de Nederlandse taal
Course module: 2IMV20
Course info
Course module2IMV20
Credits (ECTS)5
Course typeGraduate School
Language of instructionEnglish
Offered byEindhoven University of Technology; Mathematics and Computer Science; Computer Science;
Is part of
Business Information Systems
Computer Science and Engineering
Data Science in Engineering (CSE)
Contact persondr. M.A. Westenberg
Responsible lecturer
dr. M.A. Westenberg
Feedback and reachability
Other course modules lecturer
Contactperson for the course
dr. M.A. Westenberg
Other course modules lecturer
Academic year2016
2  (14/11/2016 to 05/02/2017)
Starting block
TimeslotA2: A2 - Mo 3-4, Th 7-8
Course mode
Registration openfrom 15/06/2016 up to and including 23/10/2016
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
Registration open for students from other department(s)Yes
Waiting listNo
Number of insufficient tests-
Number of groups of preference0
Learning objectives
The aim of this course is to introduce students to the theory and practice of data visualization. The course is intended for students who already have a good knowledge of programming and data structures, and a basic knowledge of linear algebra, calculus,and compter grahpics. At the end of the course, the students should be familiar with the aims and problematics of data visualization, and have a good knowledge of the theory, principles, and methods which are frequently used in practice in the construction and use of data visualization applications. Moreover, the students should be able to design, implement, and customize a data visualization application of average complexity in order to get insight in a real-world dataset from one of the application domains addressed during the lecture. On a practical side, the students should understand (and
apply) the various design and implementation trade-offs which are often encountered in the construction of visualization applications.
The course covers the theory and practice of data visualization.
This addresses several technical topics, such as: data representation; different types of grids; data sampling, interpolation, and reconstruction; the concept of a dataset; the visualization pipeline. In terms of visualization application, several examples are treated, following the different types of visualization data: scalar visualization, vector visualization, tensor visualization. Besides these, several additional topics are treated, such as volume data visualization and a brief introduction to information visualization. The techiques treated in the course are illustrated by means of several practical, hands-on, examples.
Entrance requirements
Entrance requirements tests
Assumed previous knowledge
2IL05 - Data structures
2IP05 - Programming
2IP15 - Programming methods
2IV10 - Computergrafiek
2WF08 - Lineaire algebra B
Previous knowledge can be gained by
Resources for self study
Bachelor College or Graduate School
Graduate School
URL study guide
URL study guide
Required materials
Recommended materials
Geselecteerde papers.
Instructional modes
College / course


Test weight100
Minimum grade6
Test typeAssignment(s)
Number of opportunities1
OpportunitiesBlock 2
Test duration in minutes-


Two assignments covering the core topics of the course

Kies de Nederlandse taal