Popis predmeta

Course Description

Introduction to data visualisation. The purpose and principles of data visualisation. What, how and why to visualise data. Basic visualisation techniques and tools. Visualisation of univariate, bivariate and multivariate data. Visualisation of temporal, hierarchical, textual and geo-spatial data. Visualisation of linked data, trees, graphs and networks.

Learning Outcomes

  1. explain the basic elements of a data visualization
  2. propose the design of a data visualisation
  3. create an effective data visualisation using appropriate tools
  4. critically assess the design of a data visualisation

Forms of Teaching

Lectures

Independent assignments

Week by Week Schedule

  1. Data and image models
  2. Graphical perception
  3. Visual coding
  4. Color, animation, interaction
  5. Visualization toolkits
  6. Multivariate data visualization
  7. Multivariate data visualization
  8. Midterm exam
  9. Temporal data visualization
  10. Hierarchical data visualization
  11. Textual data visualization
  12. Geo-spatial data visualization
  13. Graph and tree visualizations
  14. Network and linked data visualization
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (1. semester) (3. semester)
Communication and Space Technologies (profile)
Free Elective Courses (1. semester) (3. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Engineering (profile)
Elective Course of the Profile (1. semester) Elective Courses of the Profile (3. semester)
Computer Science (profile)
Free Elective Courses (1. semester) (3. semester)
Control Systems and Robotics (profile)
Free Elective Courses (1. semester) (3. semester)
Data Science (profile)
Elective Courses of the Profile (1. semester) (3. semester)
Electrical Power Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (1. semester) (3. semester)
Electronic and Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electronics (profile)
Free Elective Courses (1. semester) (3. semester)
Information and Communication Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Network Science (profile)
Elective Courses of the Profile (1. semester) (3. semester)
Software Engineering and Information Systems (profile)
Elective Course of the profile (3. semester) Elective Course of the Profile (1. semester)

Literature

(.), Tufte, Edward R. The visual display of quantitative information. 2nd Edition, Cheshire, CT: Graphics press, 2001.,
(.), Sosulski, Kristen. Data Visualization Made Simple: Insights Into Becoming Visual. Routledge, 2018.,
(.), Wilkinson, Leland. "The grammar of graphics." Handbook of Computational Statistics. Springer, Berlin, Heidelberg, 2012. 375-414.,
(.), Wickham, Hadley. ggplot2: elegant graphics for data analysis. Springer, 2016.,

For students

General

ID 223735
  Winter semester
5 ECTS
L3 English Level
L1 e-Learning
30 Lectures

Learning Outcomes

  1. explain the basic elements of a data visualization
  2. propose the design of a data visualisation
  3. create an effective data visualisation using appropriate tools
  4. critically assess the design of a data visualisation

Forms of Teaching

Lectures

Independent assignments

Week by Week Schedule

  1. Data and image models
  2. Graphical perception
  3. Visual coding
  4. Color, animation, interaction
  5. Visualization toolkits
  6. Multivariate data visualization
  7. Multivariate data visualization
  8. Midterm exam
  9. Temporal data visualization
  10. Hierarchical data visualization
  11. Textual data visualization
  12. Geo-spatial data visualization
  13. Graph and tree visualizations
  14. Network and linked data visualization
  15. Final exam

Study Programmes

University graduate
Audio Technologies and Electroacoustics (profile)
Free Elective Courses (1. semester) (3. semester)
Communication and Space Technologies (profile)
Free Elective Courses (1. semester) (3. semester)
Computational Modelling in Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Computer Engineering (profile)
Elective Course of the Profile (1. semester) Elective Courses of the Profile (3. semester)
Computer Science (profile)
Free Elective Courses (1. semester) (3. semester)
Control Systems and Robotics (profile)
Free Elective Courses (1. semester) (3. semester)
Data Science (profile)
Elective Courses of the Profile (1. semester) (3. semester)
Electrical Power Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electric Machines, Drives and Automation (profile)
Free Elective Courses (1. semester) (3. semester)
Electronic and Computer Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Electronics (profile)
Free Elective Courses (1. semester) (3. semester)
Information and Communication Engineering (profile)
Free Elective Courses (1. semester) (3. semester)
Network Science (profile)
Elective Courses of the Profile (1. semester) (3. semester)
Software Engineering and Information Systems (profile)
Elective Course of the profile (3. semester) Elective Course of the Profile (1. semester)

Literature

(.), Tufte, Edward R. The visual display of quantitative information. 2nd Edition, Cheshire, CT: Graphics press, 2001.,
(.), Sosulski, Kristen. Data Visualization Made Simple: Insights Into Becoming Visual. Routledge, 2018.,
(.), Wilkinson, Leland. "The grammar of graphics." Handbook of Computational Statistics. Springer, Berlin, Heidelberg, 2012. 375-414.,
(.), Wickham, Hadley. ggplot2: elegant graphics for data analysis. Springer, 2016.,

For students

General

ID 223735
  Winter semester
5 ECTS
L3 English Level
L1 e-Learning
30 Lectures