Learning Data Science

Preface

Data science is exciting work. The ability to draw insights from messy data is valuable for all kinds of decision making across business, medicine, policy, and more. This book, Learning Data Science, aims to prepare readers to do data science. To achieve this, we’ve designed this book with the following special features:

Focus on the fundamentals

Technologies come and go. While we work with specific technologies in this book, our goal is to equip readers with the fundamental building blocks of data science. We do this by revealing how to think about data science problems and challenges, and by covering the fundamentals behind the individual technologies. Our aim is to serve readers even as technologies change.

Cover the entire data science lifecycle

Instead of just focusing on a single topic, like how to work with data tables or how to apply machine learning techniques, we cover the entire data science lifecycle—the process of asking a question, obtaining data, understanding the data, and understanding the world. Working through the entire lifecycle can often be the hardest part of being a data scientist.

Use real data

To be prepared for working on real problems, we consider it essential to learn from examples that use real data, with their warts and all. We chose the datasets presented in this book by carefully picking from actual data analyses that have made an impact, rather than using overly refined or synthetic data.

Apply concepts through case studies

We’ve ...