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

Statistics is a **key component** of a data scientist's toolbox. Unfortunately, courses and books on basic statistics rarely cover the topic from a data science perspective. The idea behind this series of lessons is to provide you a practical guide for understanding the statistical concepts that should be at the fingertips of every good data scientist.

In the data visualization lessons, we saw that we can easily obtain insights about the data using various types of plots. So where does statistics fit in? 

At a high-level, statistics is about performing a *mathy* technical analysis of the data. It helps us build on the insights gained from our visualizations by giving us the ability to perform a fine-grained and in-depth data analysis. It helps us understand the structure of our data. Having this kind of understanding is important because we can then choose and apply data science techniques that are the best fit for that shape of data. This means we let the data to do the talking; we reach conclusions that are thorough and thought out instead of based on guess work. 

Without further ado, let's dive into the world of statistics!


Python Fundamentals for Data Science

The Fundamentals of Statistics

Machine Learning 101

End-to-End Machine Learning Project

The Real Talk

Introduction