Master's degree in Statistics and Operations Research

Data Visualization - June 17th to 21st

Date:

June 17th to 21st. Afternoon, 3:00 PM to 6:00 PM

Classroom:

PC1

Instructor

Pere-Pau Vázquez

I am Associate Professor in Computer Science, in FIB, where I mainly teach courses on Scientific Visualization (Master Course), Fast Realistic Rendering (Master Course), Android Programming (Master Course), Information Visualization (for the degree in Data Science, UPC), and Computer Graphics and Interaction Design (degree in Computer Science).

My research is mainly focused in Scientific Visualization, Computer Graphics, Medical Visualization, and 3D interaction.

Language

English

Description

This course is divided in two main parts. Initially, some concepts of data visualization, and their importance in communicating information visually will be introduced. Second, we will present several techniques for the design of meaningful visualization, and some examples will be developed by the students using a tool such as QlikView or Tableau.

Course goals

  • Learning the main concepts and issues for visual communicaction (pre-attentive perception, Gestalt laws, visual representations, types of charts, glyphs...).
  • Learning the different stages and components of a visualization application: data processing, data derivation, visual design, interaction design...
  • Learn to design basic visualization systems that communicate visually from several data sources.

Course contents

  • Introduction: what is visualization?
  • Perception in Visualization
  • Basic Data Visualization Techniques
  • Tips for designing effective visualizations
  • Visualization of Multi-dimensional data
  • Case studies
  • Practical work

Prerequisites

There is no special prerequisite, though familiarity with some programming language is encouraged, to facilitate implementing small queries.

Targeted at

Students interested in visual design, data science, statistics. The goal of the course is to guide them into solving complex problems by creating self-explaining visualizations and interaction techniques for exploratory data analysis.

Evaluation

The course will be evaluated through a small practical work that will be delivered some days after the course finishes.

Computer class or student's laptop?

Student's laptop

Software requirements

Since I am afraid I cannot guarantee that the students are skilled at programming, my plan is to ask the students to develop the work using Qlik view, so the easiest way is using Qlik Sense Cloud, that is free, and its webpage is: https://www.qlik.com/us/products/qlik-sense/qlik-sense-cloud.