This is a grouped Moodle course. It consists of several separate courses that share learning materials, assignments, tests etc. Below you can see information about the individual courses that make up this Moodle course.

Visualization - B4M39VIZ

Main course
Credits 6
Semesters Summer
Completion Assessment + Examination
Language of teaching Czech
Extent of teaching 2P+2C
Annotation
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.
Study targets
To master basic methods and tools for data visualization - in the fields of scientific visualization and information visualization.
Course outlines
1. Introduction to visualization
2. Data and task categorization
3. Principles of data visualization
4. Interaction in visualization
5. Visualization of scalar fields
6. Visualization of volumetric data
7. Visualization of vector fields
8. Visualization of tabular data
9. Visualization of relational data
10. Text and software visualization
11. Visualization of geographic data
12. Time and its visualization
13. Visual data mining, visual analytics, big data
14. Spare lecture
Exercises outlines
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
Literature
1. Tamara Munzner. Visualization Analysis and Design. A K Peters Visualization Series, CRC Press, 2014.

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

Visualization - BE4M39VIZ

Credits 6
Semesters Summer
Completion Assessment + Examination
Language of teaching English
Extent of teaching 2P+2C
Annotation
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.
Study targets
To master basic methods and tools for data visualization - in the fields of scientific visualization and information visualization.
Course outlines
1. Introduction to visualization
2. Data and task categorization
3. Principles of data visualization
4. Interaction in visualization
5. Visualization of scalar fields
6. Visualization of volumetric data
7. Visualization of vector fields
8. Visualization of tabular data
9. Visualization of relational data
10. Text and software visualization
11. Visualization of geographic data
12. Time and its visualization
13. Visual data mining, visual analytics, big data
14. Spare lecture
Exercises outlines
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
Literature
1. Tamara Munzner. Visualization Analysis and Design. A K Peters Visualization Series, CRC Press, 2014.

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