What Are The Best Books About Data Science?

12 Must-Have Books in your data science library

Photo by Ed Robertson on Unsplash

Okay, without further ado: Let’s Jump up direct to the question again.

What are the best books about data science?

For your convenience, I have divided the answer into two sections:

  1. Statistics and Probability Books

2. Books on programming and tools for Data Science

So, without talking much, let’s start exploring the best data science books.

Photo by Shane Hauser on Unsplash

1. Statistics and Probability books

1. Head First Statistics: A Brain-Friendly Guide (by Dawn Griffiths)


If you need a quick dive into Statistics while also being a total newbie, I will suggest you this best book for Data Science.

Taking into account that you are an aspiring Data Scientist with a non-statistics foundation, it very well may be somewhat overpowering. This book gives a few models required to comprehend statistics without harping a lot on numerical jargon.

PS: If you ever want to get start with any programming lanuage such as Java, C or Python; Google “Head First *Programming Language name*” so you’ll find heaps of simple beginner guides.
You can purchase the book here.

2. Naked Statistics (by Charles Wheelan)


This book fills in as a starter manual for statistics. It utilizes simple language to help the readers in understanding statistical formulae without harping on their complexities.

After reading this book, you can hope to have a fundamental understanding of Statistics and build up a point of view about its experience and working.

Purchase this book from here

3. Introduction to Statistical Learning-by Gareth James


In the wake of getting a handle on the fundamental concepts of Statistics, you are prepared to learn Statistics in its crude, genuine structure. It will give you knowledge of various statistical methods used in Machine Learning. In this way, connects the hypothetical ideas of Statistics with real-world applications.

This book won’t just reinforce your essentials in Statistics yet will likewise permit you to implement them in practical scenarios using R.

You can purchase this book from here

4. Practical Statistics for Data Scientists- (by Peter Bruce)


This book is for aspiring Data Scientists with no proper training in Statistics. Besides, this book gives instances of measurable strategies using R.

It will permit you to practice the necessary concepts and furthermore sharpen your R skills. The structure of this book is in with real-world applications of Data Science.

Purchase this book from here

5. Introduction to Probability - (by Charles M. Grinstead)


It is most appropriate for beginners who wish to learn probability from scratch. This book clarifies different ideas of probability that are helpful in Data Science.

It gives itemized knowledge about Discrete and Continuous Probability, Conditional Probability, Combinatorics, Central Limit Theorem, Markov Chains, and so forth. Thusly, you will have the option to gain proficiency with the fundamental ideas of Probability and use them in solving the problems.

Purchase this book from here



As mentioned earlier, programming languages and tools are necessary ingredients required for solving Data Science problems. A Data Scientist uses a variety of tools and languages like R, Python, SQL, Hadoop, Scala etc.
An aspiring Data Scientist must peruse the accompanying books to pick up skills over a large number of the programming languages and tools.


2. Books on programming and Tools for Data Science

1. Python Crash Course- (by Eric Matthes)


This book is for total beginners in Python. While Python is simpler to learn, it is hard to ace. This book is intended for individuals who need to rapidly learn Python so as to bounce into Data Science.

This book in isolated into two sections: The first part shows you Python through different concepts like conditions, loops, dictionaries, lists, etc. The second part centers around building different projects utilizing Python.

You will likewise find out about different Python libraries utilized in the analysis, visualization and web application development. Generally, this book is perfect for individuals who wish to learn Python in one proceed to actualize their knowledge in real-world scenarios.

You can purchase this book from here

7. Introduction to Machine Learning with Python: A Guide for Data Scientists -(by Andreas Muller)


For Python beginners looking forward to applying Python in real-world applications of Machine Learning, this book will give them everything they need. This book will give them all that they need. This book centers around instructing Python to users so as to assist them with building their machine learning solutions.

This book will teach you popular Machine Learning algorithms and will you the basics of the scikit-learn library which is generally mainstream in Python. It won’t just teach you Python yet, in addition, the crucial of Machine Learning with the end goal for you to develop into a gifted Data Scientist. You will figure out how to assess your model and give you suggestions to develop yourself as a Data Scientist.

You can purchase this book from here

8. Hands-On Programming with R- (by Garrett Gorlemund)


R is the most statistically oriented programming language for Data Science. This book will provide you with your first lessons of R. The authors have tailored this book by keeping in mind of non-programmers. This book will walk you through some of the most basic concepts of R like objects, notations, environment, and packages.

You will learn to apply R in real-life problems and how to write the custom-built functions that you can use for solving problems.

Furthermore, the book is fully available online as an interactive book that you can read as you practice coding in R.

You can purchase this book from here

9. R for Data Science- (by Hadley Wickham and Garrett Grolemund)


This book uses R for teaching Data Science. It encourages all of you the abilities required to be a Data Scientist like data cleaning, visualization, wrangling and also introduces you to RStudio. It makes you familiar with significant packages of R like the tidy verse that is helpful in Data Science.

This book is for individuals who have perused the past book “Hands on Programming with R”. This book is explicitly intended for the undertakings that a Data Scientist must perform in his everyday routine.

You can purchase this book from here

10. Practical Data Science with R- (by Nina Zumel)


As the name suggests, this book teaches R in a very pragmatic manner through its applications in Data Science. This book takes examples from business intelligence, A/B Testing, Decision Support to give you genuine data about Data Science. The writers of this book know the different hidden tools of Data Science and have joined them all together to give the peruser an all-encompassing perspective on Data Science.

This book gets rid of all the unnecessaries and will assist you with learning just what’s imperative to etch you into a Data Scientist.

You can purchase this book from here

11. Learning SQL (by Alan Beaulieu)


This book serves as an introductory guide to SQL. It will assist you with understanding different SQL queries and apply them in true circumstances rapidly. It will teach you basic SQL queries that will help you to retrieve, manipulate and create database objects like tables.

You can purchase this book from here

12. SQL Cookbook- (by Anthony Molinaro)


This book is for people who have a simple knowledge of SQL yet need to investigate further advanced concepts. This book will show you amazing SQL queries and functions that you can use in your database. You will get familiar with the Window Function, Hierarchical Queries, advanced searching techniques, etc..

This book will be most appropriate for individuals who have the enthusiasm to investigate the most profound pieces of SQL and be capable of it.

You can purchase this book from here

I trust that every one of these books helps you to learn and assess your model. It causes you to give recommendations to learn information science in detail or to improve your Data Scientist knowledge.

I hope the information helped you. Please let me know your thoughts on these books and if there’s any more that I needed to add to this list.

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