Information visualization for learning and communication

3 credits

Who is this course for?​

In today’s society, information visualization is used in almost every domain to make data digestible, aiding in the process of turning raw data into actionable insights. However, to choose the right visualization techniques for the right data/problem is not obvious, and knowledge of how we as humans perceive the visual world around us is needed in this process. 

This course introduces the most commonly used visualization techniques for different kinds of data/problems, and what to think about when designing visualizations in terms of knowledge of human perception and cognition. You will also learn how to evaluate your visualizations empirically. You are most likely a designer, a product or service developer or a data scientist who works with digital services and products.

What will you learn from this course?

Even if you are an experienced designer, senior product and service developer or a data scientist, you will learn how to best visualize data for a given data analysis and presentation problem. You will learn how to select the best visual representation based on knowledge of human perception and cognition as well as the most commonly used visualization techniques today. You will also get a chance to develop your skills into how to empirically evaluate the expressiveness and effectiveness of your visualizations.

The course material contains the latest academic research and practical experiences from the information visualization field.

What is the format for this course?

Instruction type: The course is primarily self-paced and based on a selection of video lectures and other resources such as articles and books. Students and teachers will meet in online forums to discuss course content.

Frequency: This course is primarily self-paced and runs for 10 weeks, with 3 scheduled real-time sessions that can be attended remote.

Examination: The course is worth 3 credits and you will hand in one written assignment for examination during the course.


Course responsible:

Tove Helldin