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Mastering Data Visualization: Theory and Foundations 

  • Offered byUDEMY

Mastering Data Visualization: Theory and Foundations
 at 
UDEMY 
Overview

Learn to design amazing charts for visualization and communication for [data] science, journalism and storytelling

Duration

5 hours

Total fee

399

Mode of learning

Online

Credential

Certificate

Mastering Data Visualization: Theory and Foundations
 at 
UDEMY 
Highlights

  • 30-Day Money-Back Guarantee
  • Certificate of completion
  • Full lifetime access
  • Learn from 1 article
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Details Icon

Mastering Data Visualization: Theory and Foundations
 at 
UDEMY 
Course details

What are the course deliverables?
  • Learn to design effective data communication
  • Improve your plots up to a professional level
  • Learn to choose and design the appropriate plot for your purpose
  • Learn to create compelling graphs that do not lie
  • Learn to avoid the traps your data can fall into
  • Learn to distinguish between good, bad and wrong visualization
  • Learn the golden rules on Graphical Excellence, Integrity and Sophistication
  • Learn the most common crimes in plotting to be able to avoid them!
More about this course
  • Welcome to Mastering Data Visualization! In this course, you're going to learn about the Theory and Foundations of Data Visualization so that you can create amazing charts that are informative, true to the data, and communicatively effective. Have you noticed there are more and more charts generated every day? If you turn on the TV, there's a bar chart telling you the evolution of COVID, if you go on Twitter, boom! a lot of line charts displaying the evolution of the price of gas. In newspapers, lots and lots of infographics telling you about the most recent discovery... The reason for that is that now we have lots of data, and the most natural way to communicate data is in visual form: that is, through Data Visualization. But, have you noticed all of the mistakes in those visualizations? I have to tell you, many of the charts that I see regularly have one problem or another. Maybe their color choices are confusing, they chose the wrong type of chart, or they are displaying data in a distorted way. Actually, that happens because more and more professional roles now require to present data visually, but there's few training on how to do it correctly. This course aims to solve this gap. If there's one thing I can promise you is that, after completing this course, you'll be looking at charts at a completely different way. You will be able to distinguish good and bad visualizations, and, more importantly, you will be able to tell when a graph is lying and how to correct it. If you need to analyze, present or communicate data professionally at some point, this course is a must. Actually, even if you don't need to actually draw plots for a living, this course is hugely useful. After all, we are all consumers of data visualizations, and we need to identify when charts are lying to us. (As an example, my mother attended one of my classes and now she's spotting mistakes in a lot of the media she sees everyday!)I really encourage you to deepen your knowledge on Data Visualization. It's not a difficult topic, and we will start from the basics. You don't need any previous knowledge. I'll teach you everything you need to know along the way and we'll go straight to the point. No rambling. I really hope to see you in class!
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Mastering Data Visualization: Theory and Foundations
 at 
UDEMY 
Curriculum

Introduction

Introduction

About this course: the 5 Ws

Examples of Data Visualization

The Problem with Data Visualization

Graphical Perception

A very quick interruption...

Introduction to this Chapter

The science of human graphical perception

The Elementary Perceptual Tasks (Part 1)

The Elementary Perceptual Tasks (Part 2)

How good is your Graphical Perception?

The Ranking of the Elementary Perceptual Tasks

Identify the Elementary Perceptual Tasks

Redesigning charts

The Golden Rules of Data Visualization

Introduction to this Chapter

Graphical Excellence

Graphical Distortion

Graphical Integrity: The Lie Factor

Exercise: Calculate the Lie Factor (updated!)

Labeling and Annotation

Data Variation vs. Design Variation

The problem with dimensions

Some advice regarding dimensions

The Data-Ink Ratio

Data Density

Proportion and Scale

Statistical Traps: How not to fall in them

Correlation doesn't sell newspapers

Selection Bias and Data Attrition

The Importance of Context

The Incorrect Normalization of the Data

The Simpson's Paradox

Plots: Find the correct plot for your data

Wait, do you really need a plot?

Types of Plots

Plotting Distributions

Plotting Relationships between variables

Plotting Rankings

Comparing Part to Whole

Plotting spatial data: Maps

Plot Crimes

Introduction to the chapter

When is it okay to cut the Y-axis?

Shading the Area of a Line Plot

The Spaghetti Chart

Error bars and the Dynamite Plot

How to choose the right colors

Common mistakes with color

What Next?

Congratulations! What now?

Faculty Icon

Mastering Data Visualization: Theory and Foundations
 at 
UDEMY 
Faculty details

Clara Granell, PhD
Designation : Complex Systems Researcher & Data Visualization Expert

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