preface

 

When I graduated from data education and started working as a data scientist, I was shocked at how different the job was from what I expected based on my studies. Data was harder to come by than I imagined. There weren’t clean datasets just sitting around waiting for me to analyze them. When I did get my hands on some data, it was undocumented and full of problems. I soon found out I wasn’t the only one who had this experience, so when I started teaching data science alongside my day job, I wanted to bridge this gap between the classroom and the real world.

I’ve been teaching data topics for a number of years now, and the single most frequently asked question I get after a course is, what should I learn next? Based on my own experiences, I usually give a standard answer: solve real problems and learn by doing. I’ve given this answer so many times now that I wanted to write it down somewhere. This book is my extended answer.