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
Requirements
A basic knowledge of computers and a passion to be successful
Description
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
Overview
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
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