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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2018/2019

Visualization

The course is not on the list Without time-table
Code Completion Credits Range Language
A4M39VIZ Z,ZK 6 2+2c Czech
Lecturer:
Tutor:
Supervisor:
Department of Computer Graphics and Interaction
Synopsis:

In this course, you will get the knowledge of theoretical background

for visualization and the application of visualization in real-world

examples. The visualization methods are aimed at exploiting both the

full power of computer technologies and the characteristics (and

limits) of human perception. Well-chosen visualization methods can

help to reveal hidden dependencies in the data that are not evident at

the first glance. This in turn enables a more precise analysis of the

data, or provides a deeper insight into the core of the particular

problem represented by the data.

Requirements:

Subject related pages:

https://moodle.fel.cvut.cz/course/view.php?id=2127

Syllabus of lectures:

1. Introduction to visualization

2. Data categorization

3. Principles of data visualization

4. Vizualizace skalárních dat

5. Vizualizace objemových dat

6. Vizualizace vektorových dat

7. Vizualizace n-rozměrných dat

8. Vizualizace relačních dat

9. Text and software visualization

10. Time and its visualization

11. User interface and interaction in visualization

12. Visual data mining, visual analytics, big data

13. Trends in visualization

14. Spare lecture

Syllabus of tutorials:

1. Introduction to the course

2. Introduction to Paraview

3. Introduction to Tableau Public

4. Visualization of scalar data

5. Visualization of volumetric data

6. Visualization of vector data

7. 1st test

8. Presentations of STAR reports

9. Visualization of n-dimensional data

10. Visualization of relational data

11. 2nd test

12. Visual analytics

13. Presentations of semestral works

14. Spare seminar

Study Objective:

To master basic methods and tools for data visualization - both in the field of information visualization and scientific visualization as well.

Study materials:

1. Fayyad, U., Grinstein, G.G., Wierse, A.: Information Visualization in Data Mining and Knowledge Discovery, Morgan Kaufmann, 2002

2. Stasko,J., Domingue,J., Brown,M.H., Price, B.A.: Software Visualization, MIT Press, 1998

3. Chen, Ch.: Information Visualization and Virtual Environments,Springer, 1999

4. Tamara Munzner. Visualization Analysis and Design. A K Peters Visualization Series, CRC Press, 2014.

5. Alexandru C. Telea. Data Visualization: Principles and Practice (2nd edition). CRC Press, 2014.

Note:
Further information:
https://moodle.fel.cvut.cz/course/B4M39VIZ
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2019-07-23
For updated information see http://bilakniha.cvut.cz/en/predmet12587904.html