Fiches de cours 2018-2019

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Data visualization

COM-480

Enseignant(s) :

Benzi Kirell Maël

Langue:

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

(Approximatively)

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

Dans les plans d'études

Semaine de référence

 LuMaMeJeVe
8-9     
9-10     
10-11 INF1   
11-12    
12-13     
13-14 INF1
INF3
   
14-15    
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
 
      Cours
      Exercice, TP
      Projet, autre

légende

  • Semestre d'automne
  • Session d'hiver
  • Semestre de printemps
  • Session d'été
  • Cours en français
  • Cours en anglais
  • Cours en allemand