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10 Best Data Science Books For Beginners

Looking to jump on the data science bandwagon? Well, LearnDunia has a list of the 10 best data science books to fast-track your learning journey.

What is Data Science?

The easiest explanation of data science is working on raw data and extracting actionable insights from it.

We live in a world where data science is assuming importance by the day. The field’s exponential growth in recent years has prompted many to pursue a career in it. However, talent in the field of data science is limited, which is understandable given that the field is not for everyone.

To make sense of a random collection of data sets, data scientists apply their knowledge of statistics, probability, and programming. A career in data science is currently one of the most lucrative.

How to Learn Data Science?

If you want to learn data science, there are many sources. You can opt for both online and offline modes. If you choose the latter option then books could be an excellent resource for you. So, here are the top ten Data Science Books for beginners in 2022.

Without further ado, let’s get started!

Best Data Science Books For Beginners In 2022

1. Data Science From Scratch (2nd Edition)

Data Science from Scratch 2e First Principles with Python

Description: As a fine introduction to data science, it is one of the best books to read for beginners. The book aims to make the reader comfortable with the mathematics and statistics of data science. It is more about the hows of data science than the whys.

The author makes you write the simplest of functions to understand what is going on under the hood. That makes it an excellent way to solidify your fundamentals. The author has a humorous way of explaining topics, which makes the book an exciting read. It can also be considered a crash course in Python.

Although the book is for beginners, someone who has some background in programming in Python, statistics, algebra, and probability will get the most out of this book.

  • Originally Published- 2019
  • Author- Joel Grus

You can buy this book here.

2. R For Data Science

R for data science Import, Tidy, Transform, Visualize, And Model Data

Description: If you are looking for the best data science books for beginners with R, don’t go any further than “R for Data Science.” This book provides a solid R grounding before teaching Data Science. Also, it’s well organized and well-illustrated. It is a great option to learn programming in data science.

Unlike many other R books, this one begins with grapes, which is an excellent way to cement the fundamentals for novices. The authors also point out the potential stumbling blocks that might appear in your learning journey. By the end of the book, you’ll realize how simple it is to manipulate data.

Even though the book considers the reader to be a complete beginner, you can get more out of the book if you have some ideas about programming in R. You don’t need anything more than a few introductory classes to get the most out of this book.

  • Originally Published- 2017
  • Author- Hadley Wickham, Garrett Grolemund

You can buy this book here.

3. Data Science

Data Science (The MIT Press Essential Knowledge series)

Description: The book is a non-technical take on the subject, yet it is a must-read for anyone serious about venturing into data sciences. Why? Well, the book provides comprehensive insights into the world of data science.

It gives an excellent overview of the fundamentals of data science for beginners. Rather than a technical take on the subject, it is more of an intellectual tour of the various aspects of data science. It gives an idea of the conceptual framework required to solve problems and streamline the workflow of a data science project. Privacy regulations and discussions on ethics are well put together. Plus, the format is simple yet exciting.

The book is an introduction to the enormous applications of data science. If you are serious about a career in data science, this is an excellent place to start. Also, if you are from a non-technical background but are just curious about the subject, pick up this book to educate yourself in this field.

  • Originally Published- 2018
  • Author- John D. Kelleher, Brendan Tierney

You can buy this book here.

4. Head First Statistics

Head First Statistics A Brain-Friendly Guide

Description: If you are familiar with the other titles in the Head First series, you’ll be pretty aware of the humorous and conversational tone in the books. Perhaps the tone makes the titles so popular. Like all the other books in the series, this one too is a beginner-level take on the subject.

The unique storytelling way of introducing the basic data science concepts is intact in this book as well. The book starts from scratch with statistics and gradually builds on them at a pace suitable for novices. The topics are divided into small, digestible bites with graphics that beautifully supplement the information. The real-life examples and exercises are the cherry on top.

If you have studied statistics at school, after finishing the book, you’ll be left wondering why your teacher didn’t make the subject quite as interesting as the book does so successfully. It is among the best-selling data science books on the market. With so much information provided in an engaging fashion, isn’t that pretty obvious?

  • Originally Published- 2008
  • Author- Dawn Griffiths

You can buy this book here.

5. Python Data Science Handbook

Python Data Science Handbook Essential Tools for Working with Data

Description: As the name suggests, this book shows how Python can be used to handle large data sets in Data Science. It is a wonderful book that describes the introduction to data science in python diligently. It comes across as an ideal reference book for those working with Data Science. The book provides a clear understanding of concepts of data processing and analysis using Python.

Even though the book doesn’t go deep into any specific topic, it covers a wide range of topics, from Pandas and Matplotib to Sci-Kit-Learn. The book also beefs up your knowledge of the standard libraries. Another great thing about the book is that it doesn’t assume you know all about NumPy, Matplotlib, and Pandas. Instead, it spends a considerate amount of time teaching you about them.

If you have a basic knowledge of Python and want to use Python to explore the world of data science, this book is for you.

  • Originally Published- 2016
  • Author- Jake VanderPlas

You can buy this book here.

6. Becoming A Data Head

Becoming a Data Head How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning

Description: This is a practical guide to Data Science. The “Becoming a Data Head” is a complete guide to using Data Science at work. It is for anyone who works in this field or wants to be more valuable to their organization by implementing it at work.

To start with, the book is non-technical. The authors have done a great job of explaining complex terms to a non-technical audience. This concise read aims to teach you how to communicate your data better. The chapters on probability, statistics, regression equations, and deep learning are particularly well explained.

The book is well-organized, and the examples are thought-provoking. It clearly shows that the authors have spent considerable time selecting topics and making examples.

  • Originally Published- 2021
  • Author- Alex J. Gutman , Jordan Goldmeier

You can buy this book here.

7. Python For Data Analysis

Python for Data Analysis Data Wrangling with Pandas, NumPy, and IPython, 2nd Edition

Description: Assumingly, you already know your way around Python and OOP. Now, you are looking for a Python book on data science. In that case, “Python for Data Analysis” is one of the best data science books for you.

The book’s prime focus is the Pandas’ Python library, which presents an excellent way to process and analyze data. Other valuable libraries like NumPy, Matplotlib, and Sci-Kit-Learn are also discussed in detail in the book.

The book covers all the basics one needs to know to start programming in Python for data analysis. The examples, however, are not up to the mark. They aren’t real-world examples.

The only pre-condition is that you need to be aware of the fundamentals of Python before getting started with this book. Otherwise, this is a reasonably beginner-friendly book. Also, if you already have a project in hand, this book will come in handy as a reference guide. You can incorporate concepts easily into the project.

  • Originally Published- 2017
  • Author- Wes Mckinney

You can buy this book here.

8. Introduction to Machine Learning With Python: A Guide for Data Scientists

Introduction to Machine Learning with Python A Guide for Data Scientists (Greyscale Indian Edition)

Description: This is an excellent guide to machine learning and the theory behind some key algorithms. It is more about understanding ML with Python than doing it practically.

The book is light on mathematical details and teaches the various algorithms from scratch. It is well written, well organized, beginner-friendly, and full of examples that help cement the facts.

You can consider it a must-have book for anyone trying to learn machine learning with Python for use in data science without all the challenging mathematical aspects of the subject.

  • Originally Published- 2016
  • Author- Andreas C. Müller, Sarah Guido

You can buy this book here.

9. Big Data

Big Data A Revolution That Will Transform How We Live, Work, and Think

Description: This non-technical take on the subject is a reliable resource to learn how much data affects our daily lives without even being aware of it. The book also discusses the prospects of big data and the fields where we will see it being used extensively.

The book beautifully captures the world around us with data sets and their use to predict future behaviors. From e-commerce sites suggesting books to read to self-driving cars predicting human behavior, the book shows how big data is being employed to make all of these better.

According to the authors, using data for business gains is not something new, and the practice has been going on for over a century. They are simply defending the practice.

  • Originally Published- 2014
  • Author- Viktor Mayer-Schönberger , Kenneth Cukier

You can buy this book here.

10. The Data Science Handbook

The Data Science Handbook Advice and Insights from 25 Amazing Data Scientists

Description: The Data Science Handbook contains 25 interviews with data scientists to provide an in-depth insight into the job of a data scientist.

All of the 25 interviews are well-organized to answer almost all aspects of Data Science. The Data Scientists interviewed are a good mix of experienced, well-known, and newbies. For someone new to data science, this book could provide invaluable insight into how to reach your goal. Also, for data science practitioners, this book could show how the more experienced data scientists reached where they have.

It goes without saying that this book is mainly for future data scientists. However, someone with no prior knowledge of the field may not find the book very useful.

  • Originally Published- 2015
  • Author- Carl Shan, William Chen, Henry Wang, Max Song

You can buy this book here.

Conclusion

The field of data science is already enormous and growing. So, no one book can be sufficient for the vast subject that it is. That is why we have listed the best data science books for different levels and learning requirements. Some of the books are non-technical and provide valuable insight into data science. What other books do you think we missed? Let us know in the comments section.

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Vijay Singh Khatri

My name is Vijay Singh Khatri, and I enjoy meeting new people and finding ways to help them have an uplifting experience. I have had a variety of customer service opportunities, through which I was able to have fewer returned products and increased repeat customers when compared with co-workers.

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