1. Introduction

This tutorial is intended mostly for statisticians and enthusiasts in data science who want to learn the basics of Python and then proceed to study learn the mainstream libraries for machine learning on Python, a general-purpose programming language, which is dynamic and strong typed.

As such, we tend to compare the language with R sometimes, but, previous knowledge of R is not a requirement, think of it more as an additional help and as a way to avoid confusion for those who already know it.

The methodology applied here is a somewhat love it or hate it one: learn by examples, and in this sense, further exploration of the code by the user is strongly encouraged (and necessary, if you are serious about programming).

Despite all this, if you believe any passages here are not sufficient clear on their own or have any suggestion, do not hesitate in contacting me.