Colors for Data Science A-Z: 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
Who this course is for:
- Anybody who wants to improve their data science presentation skills
Instructors
My name is Kirill Eremenko and I am super-psyched that you are reading this!
Professionally, I come from the Data Science consulting space with experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and since starting on Udemy I have passed on my knowledge to thousands of aspiring data scientists.
From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. One of the strongest sides of my teaching style is that I focus on intuitive explanations, so you can be sure that you will truly understand even the most complex topics.
To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!
Hi there! I'm Patrycja Hannagan, but you can call me PJ.
I'm an artist and educator from Poland, currently traveling the world to paint stunning murals and mentoring those who wish to pursue their creative dreams. I graduate art school in Italy in 2013 and moved to Australia, where I be been living and working ever since. During this time I've mastered different mediums, experimented with various styles, and been commissioned for works of all sizes. Throughout the years, I've also worked in the corporate world, gaining experience in sales and account management, while doubling in teaching art classes over weekends. In 2021, I finally made the plunge and went full-time with my art and never looked back..
If you're looking to make your art your career, I'm the girl you want to work with. I'm passionate about helping others reach their creative potential and live the life of their dreams. So, let's make it all happen!
Hi there,
We are the SuperDataScience team. You will hear from us when new SuperDataScience courses are released, when we publish new podcasts, blogs, share cheat sheets, and more!
We are here to help you stay on the cutting edge of Data Science and Technology.
See you in class,
Sincerely,
SuperDataScience Team!
Hi there,
We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more!
We are here to help you stay on the cutting edge of Data Science and Technology.
See you in class,
Sincerely,
The Real People at Ligency