Mastering Data Visualization: Theory and Foundations

Mastering Data Visualization: Theory and Foundations, available at $84.99, has an average rating of 4.54, with 43 lectures, 2 quizzes, based on 2547 reviews, and has 10401 subscribers.

You will learn about 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! This course is ideal for individuals who are Programmers / Researchers / Designers that want to learn how to produce top-quality plots or Anyone who has to present data at some point! or Data Scientists or Academic scientists having to publish in scientific journals or Journalists / Data Journalists or Communication experts or Also the general public: you should know how graphs work because they're everywhere! It is particularly useful for Programmers / Researchers / Designers that want to learn how to produce top-quality plots or Anyone who has to present data at some point! or Data Scientists or Academic scientists having to publish in scientific journals or Journalists / Data Journalists or Communication experts or Also the general public: you should know how graphs work because they're everywhere!.

Enroll now: Mastering Data Visualization: Theory and Foundations

Summary

Title: Mastering Data Visualization: Theory and Foundations

Price: $84.99

Average Rating: 4.54

Number of Lectures: 43

Number of Quizzes: 2

Number of Published Lectures: 43

Number of Published Quizzes: 2

Number of Curriculum Items: 45

Number of Published Curriculum Objects: 45

Original Price: €119.99

Quality Status: approved

Status: Live

What You Will Learn

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!

Who Should Attend

Programmers / Researchers / Designers that want to learn how to produce top-quality plots
Anyone who has to present data at some point!
Data Scientists
Academic scientists having to publish in scientific journals
Journalists / Data Journalists
Communication experts
Also the general public: you should know how graphs work because they're everywhere!

Target Audiences

Programmers / Researchers / Designers that want to learn how to produce top-quality plots
Anyone who has to present data at some point!
Data Scientists
Academic scientists having to publish in scientific journals
Journalists / Data Journalists
Communication experts
Also the general public: you should know how graphs work because they're everywhere!

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!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: About this course: the 5 Ws

Lecture 3: Examples of Data Visualization

Lecture 4: The Problem with Data Visualization

Chapter 2: Graphical Perception

Lecture 1: A very quick interruption…

Lecture 2: Introduction to this Chapter

Lecture 3: The science of human graphical perception

Lecture 4: The Elementary Perceptual Tasks (Part 1)

Lecture 5: The Elementary Perceptual Tasks (Part 2)

Lecture 6: The Ranking of the Elementary Perceptual Tasks

Lecture 7: Redesigning charts

Chapter 3: The Golden Rules of Data Visualization

Lecture 1: Introduction to this Chapter

Lecture 2: Graphical Excellence

Lecture 3: Graphical Distortion

Lecture 4: Graphical Integrity: The Lie Factor

Lecture 5: Exercise: Calculate the Lie Factor (updated!)

Lecture 6: Labeling and Annotation

Lecture 7: Data Variation vs. Design Variation

Lecture 8: The problem with dimensions

Lecture 9: Some advice regarding dimensions

Lecture 10: The Data-Ink Ratio

Lecture 11: Data Density

Lecture 12: Proportion and Scale

Chapter 4: Statistical Traps: How not to fall in them

Lecture 1: Correlation doesn't sell newspapers

Lecture 2: Selection Bias and Data Attrition

Lecture 3: The Importance of Context

Lecture 4: The Incorrect Normalization of the Data

Lecture 5: The Simpson's Paradox

Chapter 5: Plots: Find the correct plot for your data

Lecture 1: Wait, do you really need a plot?

Lecture 2: Types of Plots

Lecture 3: Plotting Distributions

Lecture 4: Plotting Relationships between variables

Lecture 5: Plotting Rankings

Lecture 6: Comparing Part to Whole

Lecture 7: Plotting spatial data: Maps

Chapter 6: Plot Crimes

Lecture 1: Introduction to the chapter

Lecture 2: When is it okay to cut the Y-axis?

Lecture 3: Shading the Area of a Line Plot

Lecture 4: The Spaghetti Chart

Lecture 5: Error bars and the Dynamite Plot

Lecture 6: How to choose the right colors

Lecture 7: Common mistakes with color

Chapter 7: What Next?

Lecture 1: Congratulations! What now?

Instructors

Clara Granell, PhD
Complex Systems Researcher & Data Visualization Expert

Rating Distribution

1 stars: 6 votes
2 stars: 17 votes
3 stars: 180 votes
4 stars: 795 votes
5 stars: 1549 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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