Available courses

Please find course descriptions in Hungarian here

Data Visualization (ENG)

Responsible for Course: Gábor Palkó, PhD. habil
Assistant: Mária Timári (Centre for Digital Humanities)

Data Visualization is a course that teaches how to create visualizations that effectively communicate the meaning behind data to an observer through visual perception. We will learn how a computer displays information using computer graphics, and how the human perceives that information visually. We will also study the forms of data, including quantitative and non-quantitative data, and how they are properly mapped to the elements of a visualization to be perceived well by the observer. We will briefly overview some design elements for effective visualization, though we will not focus on the visual design needed to make attractive and artistic visualizations. This course does not require computer programming, but computer programming can be used to complete the exercises. The course will conclude with the integration of visualization into database and data-mining systems to provide support for decision making, and the effective construction of a visualization dashboard.

The course is comprised of the following elements:

  • Lecture videos. In each module the concepts you need to know will be presented through a collection of short video lectures. You may stream these videos for playback within the browser by clicking on their titles or download the videos. You may also download the slides that go along with the videos.
  • Programming assignments. There are two required programming assignments for the class. The first programming assignment is to create a visualization of numerical data, and the second programming assignment is to create a visualization of non-numerical data (e.g., a network or a hierarchy). For each assignment, sample data will be provided, but you are encouraged to find your own data. Your goal will be to present that data in a visualization that helps the observer to better understand what the data represents. The programming assignments will be peer graded based on rubrics that measure how well the course's methods have been applied to the visualization of the data.

Conditions for completing the course:

Completing the course on the Coursera site begins with listening carefully to the videos, and reading related materials. It is recommended to take notes, as the examination will not be about solving tests between parts of the course (these are not mandatory, they only give students the opportunity to practice), but an online examination after completing the course.
In addition, two project tasks (visualization of numerical and non-numerical data) are required for completion, during which students can apply what they have learned. More information on these tasks can be found on the webpage.
Through Microsoft Teams, once a week questions regarding the course material or the assignments can be discussed.

Reading list:

Tamara Munzner, Visualization Analysis and Design, CRC Press, 2014. 
Colin Ware, Information Visualization Analysis for Design (3rd Edition), Elsevier, 2013.

Creating a Digital Cultural Heritage Community (ENG)
Text encoding and the Text Encoding Initiative (ENG, HUN, ESP, FR)

Only one of the courses listed needs to be taken. To apply, please click here