Data Science Books For Beginners

Interest in data science has exploded in recent years. This area, which yesterday seemed relatively abstract, is today at the center of discussions, especially on social media. It finds applications both in politics and in the field of international law. Knowledge of data is today a skill in great demand in all sectors. Every day, we create data points that feed into large-scale BI systems.

Do you want to stay informed on the evolution of the data world? Are you entering the field of data science? Are you looking to develop your knowledge? Whatever your goal, in this article you will find a list of books intended for beginners to discover this sector. Below we have listed Data Science Books for Beginners.

Top 5 Data Science Books for Beginners

1. “The Data Science Handbook”

Often the best way to learn is to listen to the experts. And there’s no better way to expand your knowledge than by talking to 25 of the industry’s top experts! “The Data Science Handbook” is a compilation of interviews with many prominent data scientists, from the former Chief Data Officer of the United States to team leaders in large companies, to rising stars in the industry who create their own programs. The idea is to offer a unique insight into data science.

In these different interviews, beginners will find tips, lessons learned from mistakes and career development strategies to help them succeed in the world of data science. This book does not explore the technical aspects of data science and is not intended to serve as an exhaustive guide on this topic, but rather offers a set of practical and informed advice.

2. “Doing Data Science: Straight Talk from the Frontline”

“Doing Data Science” gets right to the point. It is based on Columbia University’s Introductory Data Science course, and is intended for beginners who want to explore the subject. Cathy O’Neil, data science consultant, worked with teacher Rachel Schutt to bring the content of this course to the general public.

These experts offer informative lessons on the topic, along with relevant case studies and code snippets, to present accessible examples. This book constitutes a technical resource of choice by discussing algorithms, methods, models, and visualization of data.

3. “Data Science for the Layman: No Math Added ”

Because of its many commonalities with mathematics, data science can seem inaccessible and complicated. This book serves as an introduction to data science and algorithms. By using simple terms without going into the “math” side, it makes the subject less intimidating and easier to understand.

Each chapter is dedicated to a specific and useful algorithm, the operation of which it explains using concrete examples. The many visual elements also make it easier to understand, reference sheets list the advantages and disadvantages of each algorithm and a useful glossary summarizes important terminology in data science.

4. “The Art of Data Science”

This book covers exploring data lakes and finding information. It focuses on the process of analyzing and filtering data to uncover new information. The authors draw on their experiences to help both beginners and managers in their analysis projects.

Both have already managed numerous projects and supervised teams of analysts in the professional world. They explain how to produce truly relevant results and present the pitfalls to avoid in data projects.

5. “Data Science For Dummies”

The Dummies guide series is known for explaining the smallest concepts in layman’s terms, and this data science book is no exception. It focuses on the business side of data science and serves as an introductory guide to becoming a professional in the field. It gives beginners a complete overview of the discipline, to allow them to familiarize themselves with the concepts of Big Data and with the applications of data science in our daily life.

It also explores areas such as data engineering, programming languages ​​like R and Python, machine learning, algorithms, AI, and data visualization techniques quite broadly. This book is a good place to start if you are curious about data science or if you want to gain insight into the discipline.

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