Coursebooks

Data visualization

COM-480

Lecturer(s) :

Vuillon Laurent Gilles Marie

Language:

English

Summary

Understanding why and how to present complex data interactively in an effective manner has become a crucial skill for any data scientist. In this course, you will learn how to design, judge, build and present your own interactive data visualizations.

Content

Tentative course schedule

Week 1: Introduction to Data visualization Web development

Week 2: Javascript

Week 3: More Javascript

Week 4: Data Data driven documents (D3.js)

Week 5: Interaction, filtering, aggregation (UI /UX). Advanced D3 / javascript libs

Week 6: Perception, cognition, color Marks and channels

Week 7: Designing visualizations (UI/UX) Project introduction Dos and don¿ts for data-viz

Week 8: Maps (theory) Maps (practice)

Week 9: Text visualization

Week 10: Graphs

Week 11: Tabular data viz Music viz

Week 12: Introduction to scientific visualisation

Week 13: Storytelling with data / data journalism Creative coding

Week 14: Wrap-Up

Keywords

Data viz, visualization, data science

Learning Prerequisites

Required courses

CS-305 Software engineering (BA)

CS-250 Algorithms (BA)

CS-401 Applied data analysis (MA)

Recommended courses

EE-558 A Network Tour of Data Science (MA)

CS-486 Human computer interaction (MA)

CS-210 Functional programming (BA)

Important concepts to start the course

Being autonomous is a prerequisite, we don't offer office hours and we won't have enough teaching assistants (you've been warned!).

Knowledge of one of the following progrmaming language such as C++, Python, Scala.

Familiarity with web-development (you already have a blog, host a webiste). Experience with HTML5, Javascript is a strong plus for the course.

Learning Outcomes

By the end of the course, the student must be able to:

Transversal skills

Teaching methods

Ex cathedra lectures, exercises, and group projects

Expected student activities

Assessment methods

Supervision

Office hours No
Assistants No
Forum No

Resources

Bibliography

Visualization Analysis and Design by Tamara Munzner, CRC Press (2014). Fee online version at EPFL.

Interactive Data Visualization for the Web by Scott Murray O'Reilly (2013) - D3 - Free online version.

Ressources en bibliothèque
Notes/Handbook

Lecture notes

Websites
Moodle Link

In the programs

  • Communication Systems - master program, 2019-2020, Master semester 2
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Communication Systems - master program, 2019-2020, Master semester 4
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Computer Science - Cybersecurity, 2019-2020, Master semester 2
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Computer Science - Cybersecurity, 2019-2020, Master semester 4
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Computer Science, 2019-2020, Master semester 2
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Computer Science, 2019-2020, Master semester 4
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Data Science, 2019-2020, Master semester 2
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Data Science, 2019-2020, Master semester 4
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Digital Humanities, 2019-2020, Master semester 2
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Digital Humanities, 2019-2020, Master semester 4
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Electrical and Electronics Engineering, 2019-2020, Master semester 2
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Electrical and Electronics Engineering, 2019-2020, Master semester 4
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Data science minor, 2019-2020, Spring semester
    • Semester
      Spring
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks
  • Electrical Engineering (edoc), 2019-2020
    • Semester
      Fall
    • Exam form
      During the semester
    • Credits
      4
    • Subject examined
      Data visualization
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Project
      2 Hour(s) per week x 14 weeks

Reference week

MoTuWeThFr
8-9
9-10
10-11
11-12
12-13
13-14
14-15
15-16
16-17
17-18
18-19
19-20
20-21
21-22
Under construction
Lecture
Exercise, TP
Project, other

legend

  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German