When the world is consumed, once again, by pseudo-scientists and flat-earth conspiracists, it is time to go back to the drawing board. And, as they say, numbers don’t lie. Several companies in many fields are starting to deploy fact checkers and data scientists to help out with understanding their consumers and/or target audience better. Data sciences are crucial even for those who want to manipulate the system.

If you're interested in becoming a data scientist or learning more about data science, you're in the right place. Let's see what the best data science books are that will help you learn everything you need to know.

Best Data Science Books

Whichever side of the argument you’re on, it is important to know the basics of data mining, cleaning, organizing, and presenting. Here is a list of books that will help to get started on that path, whether you want to improve your understanding for the sake of professional growth or just to keep your brain sharp.  

Head First Statistics: A Brain-Friendly Guide by Dawn Griffiths

Head First Statistics: A Brain-Friendly Guide by Dawn Griffiths

This is a statistics book that has as many theories as illustrations. You will be able to learn about what is considered to be a relatively dry subject through histograms and probability distributions. This is a great book for those who want to learn statistics through interactive material. The book has puzzles, stories, quizzes and even case studies. 

It is recommended for both students who want to prepare for a career in statistical analysis and also professionals who want to brush up their skills while on the job. It is also a good one for high school students who want to take the College Board’s Advanced Placement (AP) Statistics Exam. The book is geared to explain crucial theories in a way that makes it a piece of cake to use them. 

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R for Data Science by Hadley Wickham and Garrett Grolemund

R for Data Science by Hadley Wickham and Garrett Grolemund

R for Data Science is a great book for those who want to learn about turning raw data into information that will help companies and/or individuals make informed decisions. It serves as an introduction to R, RStudio and a collection of R packages that are made for data scientists. You are not expected to have any prior knowledge to read this book. It is also recommended for those who have no experience in programming. 

It is sort of a step-by-step guide to importing, exploring and modeling your data and presenting the results in an easily communicable manner. You will be able to understand the cycle of data science and equip yourself with the required tools. The book also comes with a lot of exercises so that you can practice what you have learned. 

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Practical Statistics for Data Scientists by Peter Bruce and Andrew Bruce 

Practical Statistics for Data Scientists by Peter Bruce and Andrew Bruce

Statistics is a big part of data science. But not many are proficiently trained in the subject. If you’re learning to get an edge professionally, this is your chance. This book by Peter Bruce and Andrew Bruce is an excellent choice for those who want to learn basic statistics. 

Unlike this piece, this book is not about philosophy. It teaches you the practical ways of statistics and when the time is right, it gives you advice on how to avoid misusing those principles. It is a great copy that helps you put statistics in perspective. By the time you finish this book, you will be able to do data analysis which is the first step in data science. You will be able to use random sampling for big data. You will know the principles that help you design experiments and get definitive answers.  

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Python for Data Science by Ethan Williams 

Python for Data Science by Ethan Williams

If you have any proficiency in Python programming in the context of data science, this book will be your comprehensive guide in taking it forward. But it is also a good book for beginners to pick up. You will be able to learn basic concepts of data science even if you know a programming language that is not Python.  

You will be introduced to some Python libraries to help you with data analysis and visualization. There are a lot of practical examples and applications to help you relate to the lessons. You will also find exercises whenever it makes sense to have them. You will get a full learning experience thanks to the book and the practice materials in it. The writer is confident that any limitations you might experience are caused by your own self. 

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Best Practices in Data Cleaning: A Complete Guide to Everything You Need to Do Before and After Collecting Your Data by Jason W Osborne

Best Practices in Data Cleaning: A Complete Guide to Everything You Need to Do Before and After Collecting Your Data by Jason W Osborne

Every research process starts with collecting and cleaning data. And yet, many researchers skip the cleaning process. This could have disastrous consequences. In the process of avoiding such rookie mistakes, this book is the first step. Jason W Osborne’s handbook lays out a step-by-step way of implementing the best practices when it comes to collecting data, testing assumptions, examining it and cleaning the data to eliminate as many errors as possible before putting it to test.

The book also has suggestions that are not only easy to implement but are based on empirical evidence on each topic. So ignore it at your own risk. 

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Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures by Claus O Wilke

Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures by Claus O Wilke

It is not enough to know how to collect and examine data. Visualizing it in a way that can be presented to make a case is just as important a step, no matter the field of work. Such communication is not an impossible skill to learn. But when you are dealing with a large dataset, you will need some techniques in your pocket to be able to break down its complexity. That’s where this book by Claus O Wilke comes into play.  

Today, the skill to visualize data is an asset across industries. Engineers, scientists and business analysts are just the beginning of that story. This book has some practical solutions for everyone who wants to get better at the game. You will also learn about the different kinds of visualizations and how to pick the one that is best to tell the story you want to tell. You will also gain an understanding of the aesthetics of visual representation. 

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Bottom Line: Best Data Science Books

Data is widely used in many industries today. To gain an edge in the employment market, you need to up your game just a little bit. That doesn’t mean you have to bury yourself in student loans and enroll yourself in expensive courses that will keep you out of the job market for many months to come. 

Sometimes, all you need is a little old-fashioned reading material and some quiet time in a corner of the house. We hope that’s exactly what this list of best data science books will help you do.

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