books datascience reading

14 Essential Books to Break Into a Data Science Career in 2021

If there was one thing that stole the limelight in Linkedin’s 2020 Emerging Jobs Report for any country, it was the mention of AI Specialists and Data Scientists in the top 3 roles.

As now companies have also begun to realize the power of data, we can expect to see more job postings and higher salaries in these job roles in 2021. Keeping this in mind, we decided to curate a list of 14 essential books that will help you understand this domain better. 

You can read these books, regardless of your skill-level or educational background. These data science books will be helpful for data science professionals and enthusiasts alike.

So, let’s get started!

Here are the 14 essential data science books that can help you grab one of the hottest job of this century:

  • The Elements of Statistical Learning — Data Mining, Inference, and Predictionby Trevor Hastie, Robert Tibshirani, Jerome Friedman

A valuable resource for anyone who is interested in statistics, this book uses a statistical approach to describe important ideas in different fields. It covers topics from supervised to unsupervised learning, neural networks, support vector machines, and more.

  • The Art of Statistics — How to Learn from Data, by David Spiegelhalter

This book, written by a world-renowned statistician, shows readers the art of deriving knowledge from raw data by focussing on the concepts and connections that shape math. This book not only shows how mathematicians solve statistical science to solve problems but also teaches us to think like them!

  • Practical Statistics for Data Scientist — 50+ Essential Concepts Using R and Python, by Peter Bruce, Andrew Bruce, and Peter Gedeck

This is a practical guide that explains how to apply various statistical methods to data science, without their misuse. It also gives sound advice on what’s important and what’s not. This is a perfect data science book to get a deeper statistical perspective.

  • Data Science for Beginners, by Andrew Park

Created with a beginner in this field in mind, this powerful read delves deep into the fundamentals behind Python and Data Science. This data science book will help you discover everything you need to get started.

  • Data Science for Business — What You Need to Know about Data Mining and Data Analytic-Thinking, by Foster Provost and Tom Fawcett

Written by renowned data science experts, this book introduces the fundamentals of data science and also helps you walk through the data based analytical thinking. This approach is important for getting useful knowledge and business value from the data.

  • Build a Career in Data Science, by Emily Robinson and Jacqueline Nolis 

This data science book will be your companion in landing your first data science job and developing to a managerial role. It covers topics such as adapting to company needs, preparing for a management role, lifecycle of a typical data science project.

  • Clean Code — A Handbook of Agile Software Craftsmanship, by Robert C. Martin

This is a revolutionary data science book that has helped thousands of programmers in developing clean code. This book will allow you to think about what’s right about the code, what’s wrong with it, and will even give you a path to reassess your professional values.

  • The Art of Data Science — A Guide for Anyone Who Works With Data, by Roger D. Peng and Elizabeth Matsui

This data science book describes the process of analyzing data. Applicable to both practitioners and managers in data science, it provides an amazing overview of the data analysis workflow. It also gives an effective overview of how data analysis is primarily an art that involves iterative processes, with information learned at every step.

  • A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming Skills (2nd Edition), by Jay Wengrow

This is a practical guide to understanding data structures and algorithms. It goes beyond theory and will help you in improving your programming skills. From learning how to use hash tables, trees, and graphs, to improving the efficiency of your code: you’ll learn it all in this data science book.

  • Deep Learning with Python, by Francois Chollet

Written by the creator of Keras and Google AI researcher, this book will introduce you to the field of deep learning using Python and Keras library. It consists of intuitive explanations and practical examples that will give you a good platform to understand the concept of deep learning.

  • Foundations of Deep Reinforcement Learning — Theory and Practice in Python, by Laura Graesser and Wah Loon Keng

This data science book is for anyone who has advanced knowledge of machine learning and wants to solve more complex problems using deep reinforcement learning. It is ideal for students and software engineers who have a working understanding of Python. 

  • Big Data — A Revolution That Will Transform How We Live, Work, and Think, by Victor Mayer-Schonberger

This book has been a finalist in the Financial Times Business Book of the Year. Big Data is an important and one of the first major books about this concept. It has 2 leading experts explaining what big data is, and how it will impact our lives in the years to come.

  • Fundamentals of Data Visualization — A Primer on Making Informative and Compelling Figures, by Claus O. Wilke

This data science book takes you through commonly encountered visualization problems and offers guidelines to turn large datasets into clear figures. It can help you understand the rationale behind effective visualization and also teach you to design more meaningful plots that get the right message across.

  • Storytelling with Data — A Data Visualization Guide for Business Professionals, by Cole Nussbaumer Knaflic

This data science book will teach you how to communicate effectively with data. It will help you understand the fundamentals of data visualization and is definitely a must-read book for anyone who wants to present information in a clear, brief, and graphical way.

Final Words

We’re sure these books will allow you to venture into the world of data science as you enter the year 2021.

Shared Via Priyanka Pant

Recommended posts

#DSBreakdown: What are the hottest fields in IT right now?

As the world of tech continues to evolve at an unprecedented rate, the demand for professionals with advanced skill sets in IT and data

9 Best Practices Every Data Science Leader Should Follow

Being a data scientist is hard. In addition to the combination of advanced mathematics and coding skills required to do the job, it’s a

But first, cookies

We use cookies to improve your experience and deliver personalized content. By using this website, you agree to our Privacy Policy.
New podcast: An Interview with Tom van Wees and Roderick de Koning, CCO and CEO of Ginger Payments