Colors for Data Science AZ Data Visualization Color Theory

Learn how to apply colour theory to improve your Data Science & Analytics data visualisations and presentations
Colors for Data Science AZ Data Visualization Color Theory
File Size :
2.07 GB
Total length :
3h 46m



Kirill Eremenko


Last update




Colors for Data Science AZ Data Visualization Color Theory

What you’ll learn

Use colour schemes to create eye-catching palettes
Assess colour aesthetics of any Data Visualization
Know the difference between RGB vs CMYK
Create impactful Data Science visualizations
Understand how colour schemes work
Know what a tint, shade and tone are
Know what an achromatic colour is
Use tools such as Adobe Color, Paletton and ColorBrewer

Colors for Data Science AZ Data Visualization Color Theory


A basic knowledge of computers and a passion to be successful


A fun and entertaining journey thorough colour theory and basic colour knowledge to help you create effective Data Science visualisations.
So why is this an important course for a Data Scientist?
Think about this…
You’ve just completed an incredible Analytics project.
You did the data prep, the modeling, and now you have the insights.
But we all know that this is not the end…
You still need to present your findings to your manager, client or even a large audience.
Now this is where the trick is.
A powerful visualization can make or break your project.
And this is where the power of colours comes in!
In this course we will show you where colours originate from and what they mean.
You will finally understand how to make your Data Science visualizations and presentations super-impactful.
Whether you are a beginner or a seasoned Data Scientist, this course will help you truly wow your audience and take your Analytics skills to the next level.
We can’t wait to see you inside!
Kirill & Patrycja


Section 1: Introduction

Lecture 1 Welcome to the course

Section 2: Color Theory

Lecture 2 Color Theory Map

Lecture 3 What is a color?

Lecture 4 The Color Wheel

Lecture 5 Tints, Shades and Saturation

Lecture 6 Achromatic Colours

Lecture 7 CMYK vs RGB

Lecture 8 Colour Blindness

Section 3: Colours & Emotions

Lecture 9 Why this section is important

Lecture 10 Meanings of Colours

Lecture 11 Warm and Cool Colours

Lecture 12 Yellow Orange Red

Lecture 13 Blue Green Purple

Section 4: The Tools

Lecture 14 Hello! This is what you will learn in this section

Lecture 15 Adobe Color

Lecture 16 Paletton

Lecture 17 Color Brewer 2.0

Section 5: Colour Schemes

Lecture 18 Colour Context

Lecture 19 Colour Schemes

Lecture 20 Monochromatic Colour Schemes – REAL Data Examples

Lecture 21 Analogous Colours – REAL Data Examples

Lecture 22 Complementary & Split-Complementary Colours – REAL Data Examples

Lecture 23 Triadic & Tetriadic Colours – REAL Data Examples

Lecture 24 Colour of the background

Section 6: Data Science Project Walkthrough

Lecture 25 Project Brief: Vitamin Trials

Lecture 26 Download & install Tableau Public

Lecture 27 Buildining the visualization

Lecture 28 Testing out color palettes

Lecture 29 Applying the split complementary color scheme

Lecture 30 Coloring the subcategories

Lecture 31 Applying the triad color scheme

Lecture 32 Applying the analogous colour scheme

Lecture 33 Section recap

Section 7: Bonus Section

Lecture 34 Your Super-Special Invitation

Anybody who wants to improve their data science presentation skills

Course Information:

Udemy | English | 3h 46m | 2.07 GB
Created by: Kirill Eremenko

You Can See More Courses in the Business >> Greetings from

New Courses

Scroll to Top