Ready Before Run()

A Practical Guide to Gear Up for Data Science

1 Welcome

Welcome to “Ready Before Run(): A Practical Guide to Gear Up for Data Science.” This guide is designed for readers from diverse backgrounds - economists, statisticians, engineers, and beyond - who are interested in producing advanced analytics workflows, but don’t necessarily have any computer science foundations.

If you’ve found this resource, you likely already possess strong analytical skills from your domain. What you may lack is familiarity with the technical infrastructure that supports modern data science work. Just as a chef needs a well-equipped kitchen before creating a culinary masterpiece, data scientists need properly configured tools before they can transform data into insights.

This guide will walk you through setting up the essential components of a data science environment—from programming languages and version control to visualization tools and cloud platforms. By the end of this journey, you’ll have a robust technical foundation that will allow you to spend less time battling your infrastructure and more time materializing your ideas.

2 Preface

I think it’s worth noting that the embers to write this book began to glow in a pre-AI era—an age where the Harvard Business Review regarded Data Scientist as the “sexiest job of the 21st century.” Much has changed over the last few years, and it would be remiss of you not to question the relevance of data scientists today. I believe that even with the advent of AI, now, more than ever, it is critical to understand the mechanics of data science so that we can become more responsible, productive analytics professionals. While machines may remove much of the grunt work that so many have been so well paid for over the last 15 years, if we do not understand what the machines are doing or how to make use of the output the machines provide us, or indeed how to ask the machines for the things we need, we cannot hope to remain relevant in our respective fields.

This book grew out of my experience as an analyst and the recognition that many people who require advanced data processing struggle not with analytical concepts, but with the technical infrastructure needed to apply those concepts effectively. While there are countless resources teaching statistical methods, machine learning algorithms, and data manipulation techniques, relatively few focus on the foundation setup that makes this work possible.

“Ready Before Run()” fills this gap by providing clear, practical guidance for establishing your data science workspace. Rather than diving immediately into coding, we’ll first ensure you have the proper environment configured—allowing you to build technical confidence before tackling analytical challenges.

The book is structured as a step-by-step guide, beginning with basic command line operations and progressing through programming language setup, version control, visualization tools, and more advanced topics like containerization and cloud computing. While each chapter builds on the previous one, they are written to be referenced independently if needed.

My hope is that this book serves as your resource to lower any technical barriers you may face and provide a comprehensive foundation for your data science journey. Let’s free you from your infrastructure burdens, allowing you time to concentrate on developing your analytical expertise and making meaningful contributions in your field.

Ready? Let’s gear up for data science!

Cesaire Tobias
LinkedIn