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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
Who this course is for:
Anybody who wants to improve their data science presentation skills

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

  • You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
  • No previous design experience is needed.
  • No previous Adobe XD skills are needed.

Course Content

27 sections • 95 lectures
Expand All Sections
1-Introduction
1
1.1-Welcome to the course
2-Color Theory
8
2.1-Color Theory Map
2.2-What is a color?
2.3-The Color Wheel
2.4-Tints, Shades and Saturation
2.5-Achromatic Colours
2.6-CMYK vs RGB
2.7-Colour Blindness
2.8-Colour Theory
3-Colours & Emotions
6
3.1-Why this section is important
3.2-Meanings of Colours
3.3-Warm and Cool Colours
3.4-Yellow Orange Red
3.5-Blue Green Purple
3.6-Colours and Emotions
4-The Tools
4
4.1-Hello! This is what you will learn in this section
4.2-Adobe Color
4.3-Paletton
4.4-Color Brewer 2.0
5-Colour Schemes
8
5.1-Colour Context
5.2-Colour Schemes
5.3-Monochromatic Colour Schemes - REAL Data Examples
5.4-Analogous Colours - REAL Data Examples
5.5-Complementary & Split-Complementary Colours - REAL Data Examples
5.6-Triadic & Tetriadic Colours - REAL Data Examples
5.7-Colour of the background
5.8-Colour Schemes
6-Data Science Project Walkthrough
9
6.1-Project Brief: Vitamin Trials
6.2-Download & install Tableau Public
6.3-Buildining the visualization
6.4-Testing out color palettes
6.5-Applying the split complementary color scheme
6.6-Coloring the subcategories
6.7-Applying the triad color scheme
6.8-Applying the analogous colour scheme
6.9-Section recap
7-Congratulations!! Don't forget your Prize :)
1
7.1-Bonus: How To UNLOCK Top Salaries (Live Training)