Gain insights into data science with easy-to-follow, hands-on explanations. Explore essential concepts quickly and efficiently, even without prior statistics knowledge, for a career boost.

GrokkingDataScientist.tar.gz

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Master the skills that can get you a $100K+ salary even if you bunked your statistics classes. 

No need to waste hours and hours on browsing from one article to the next and piecing together the info you need to grasp important topics. No need to get overwhelmed by the information overload. Find easy to follow, hands-on, and fun explanations of all the essential topics in one place so you can quickly and efficiently learn what you need to thrive as a data scientist.

"Is this course right for me?" Continue to read to decide for yourself!

- "I want to understand this data science concept. Let me Google it". Then after hours of surfing, reading random articles, and invoking the heavens, you are more confused than before.
- "Data science is the sexiest and highest paying job of the 21st century. I want to become a data scientist too".
- "I have a basic knowledge of Python, willingness to learn, and commitment to become a great data scientist."

Is that you? If yes, you are at the right place.

Grokking Data Science

### Picking the Right Data Visualization

Picking the right visualization technique can be tricky. Your data could technically work well with multiple types of plots, but you need to pick the one that ensures ***your message is clear, accurate, and concise***. 

In general, line, bar, and column charts are good to represent change over time. Pie charts can show parts-of-a-whole, and scatter plots are nice if you have a lot of data. 

To make your life easier here is a cool cheat sheet on selecting the  right visualization methods from the Harvard CS-109 extension program:



# Picking the Right Data Visualization

Picking the right visualization technique can be tricky. Your data could technically work well with multiple types of plots, but you need to pick the one that ensures ***your message is clear, accurate, and concise***. 

In general, line, bar, and column charts are good to represent change over time. Pie charts can show parts-of-a-whole, and scatter plots are nice if you have a lot of data. 

To make your life easier here is a cool cheat sheet on selecting the  right visualization methods from the Harvard CS-109 extension program:



Python Fundamentals for Data Science

The Fundamentals of Statistics

Machine Learning 101

End-to-End Machine Learning Project

The Real Talk

Data Visualization Cheat Sheet

Picking the Right Data Visualization