Data Science Crash Course 2/10: Anaconda and Jupyter Notebooks

Let’s learn Data Science in 2020.

Welcome to the second instalment of Data Science Crash Course. This text will be about setting up a framework for Data Science experiments. I’m assuming you have no knowledge of programming to make everything smooth and easy. Let’s begin.

Jupyter Notebooks are a great Data Science tool. They come with Anaconda.

Anaconda

Anaconda is a free, open-source distribution of both Python and R programming languages for data science and machine learning applications. It aims to simplify package management and deployment.

Ok, that might sound complicated but the truth is, it’s all about giving you a framework where you can code. You need a compiler to run Python code, think text editor which ‘runs’ your program, and Anaconda gives you that plus much more. It gives you all packages you might want to use and Jupyter Notebooks.

But let’s start with installation. Let’s go to www.anaconda.com and download the most recent version:

Now that you have it, it’s time to get into more explanations how it all works.