1. Introduction: Data Science for Not-Yet-Scientists

In today’s world, data is generated at an unprecedented pace, and our ability to harness it is changing the way we live, work, and even think. Data science, the interdisciplinary field that blends statistics, computer science, and domain-specific knowledge, empowers us to extract insights from this vast ocean of data. As data science becomes increasingly essential across various industries and sectors, there is a growing need for skilled professionals who can make sense of data and transform it into actionable information. This book is designed to be your guide in this exciting and fast-evolving field.

There are numerous data science books, courses, and materials available, catering to different levels of expertise and backgrounds. However, many of these resources assume a strong foundation in computer science, math, or quantitative scientific disciplines. This is because until very recently, such career shifts were the typical path to becoming a data scientist (which also holds for the author of this book). But more and more universities or higher educational programs are starting to aim at the formation of a new generation of data scientists. Students who have no prior IT-related formation or scientific degrees. This book is for them! It fills the described gap by providing a comprehensive, hands-on introduction to data science for those who are just starting their journey or considering a career in this fascinating domain.

What sets this book apart from other resources is its focus on accessibility and practicality. We’ve designed it to be understandable to new undergraduate students, with only basic Python programming and math skills as requirements. You don’t need to be an expert in computer science or have a strong background in statistics to grasp the concepts and techniques covered in this book.

Throughout the chapters, you’ll find a wealth of hands-on examples and exercises that will help you develop a deep understanding of data science concepts and techniques. By working through these practical examples, you’ll be able to apply your newly acquired knowledge to real-world situations, making you better equipped to tackle data-driven challenges in your chosen field.

We firmly believe that becoming proficient in data science is within reach for anyone who possesses a combination of intellectual curiosity, a passion for learning, and a knack for logical puzzles or detective work. Additionally, a basic affinity for math and statistics goes a long way. Your academic or professional background doesn’t define your potential in data science. Rather, your perseverance, your willingness to engage with complex problems, and your commitment to continuous learning will be your guiding stars.

This book represents our endeavor to dismantle any perceived barriers in your way, aiming to make data science comprehensible and accessible to a wide range of readers. We aim to empower aspiring data scientists to acquire and master the essential skills needed in an increasingly data-driven world.

So, are you ready to embark on your data science journey? Let’s dive in and learn how to do the detective work of a data scientist to extract new knowledge from complex data.