Data Science has emerged to become one of the most paid and highly reputed domains for professionals. As we see more and more companies adopting data science applications in their businesses, there is a surge in the requirement for skilled data science professionals. If you are considering making a move in this domain, or are a data science expert who wants to remain on top of things, here is a list of books for you to keep the ball rolling. 

Top 9 Data Science Books for Beginners

  1. Practical Statistics for Data Scientists
  2. Introduction to Probability
  3. Introduction to Machine Learning with Python: A Guide for Data Scientists
  4. Python for Data Analysis
  5. Python Data Science Handbook
  6. R for Data Science
  7. Understanding Machine Learning: From Theory to Algorithms
  8. Deep Learning
  9. Mining of Massive Datasets

Practical Statistics for Data Scientists – By Peter Bruce and Andrew Bruce

Data Science Books - Practical Statistics for data scientists

This book is ideal for absolute beginners. It covers a vast range of topics critical to the field of data science in an easy to understand language. You can learn a lot about statistics in data science and could cover in-depth on topics like randomisation, distribution, sampling etc. If you are starting from scratch, this book is for you. 

Introduction to Probability – By Joseph K. Blitzstein and Jessica Hwang

data science books - introduction to probability

Next in line after statistics is probability. It holds immense importance in the field of data science and this book will introduce you to the concepts by taking examples from real-life problems. If you have studied basic probability in school, this book is a build upon it. If you are studying probability for the very first time, you just need to spend some extra time with it. This book covers core concepts and will help you build a strong foundation for data science. 

Introduction to Machine Learning with Python: A Guide for Data Scientists – By Andreas C. Müller and Sarah Guido

data science books - introduction to ML with Python

Knowledge of Machine Learning is critical for a data science professional. This book helps you cover the basics of Machine Learning. If you practice along with the book for a substantial time, you would end up building machine learning models on your own. This book has all the examples with Python, but even if you do not have prior knowledge of Python programming language, you will be able to learn it through this book. This book is for beginners to understand the basics of ML and Python. It is recommended that when you are through with this book, you pick up an advanced level book to learn more about both Machine Learning and Python.

Python for Data Analysis – By Wes McKinney

data science books - python for data analysis

Apart from Machine Learning, Python is also a popular programming language in Data Analytics. Also, data analytics is critical to data science. Hence this book is a complete guide for beginners in data science to learn the concepts of Data Analytics with Python. The book is fast-paced yet simple. You can expect to be building real applications within a week with the help of this book. It is amazingly structured and organised for the readers and gives a peek into the world of data analysts and data scientists, and the kind of work the indulge into in their role. 

Data Science Books for Intermediate Level

Python Data Science Handbook – By Jake VanderPlas

data science books - Python Data Science Handbook - By Jake VanderPlas

This book is a great recommendation for those who have covered the basics of Python and are ready to explore and work with Python libraries. Python Data Science Handbook is an in-depth guide into all standard Python libraries such as Pandas, Numpy, Matplotlib, Scikit-learn and more. 

R for Data Science – By Hadley Wickham and Garret Grolemund

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

R is another popular programming language for Data Science applications. For those who have worked on Python, the next step is to implement data science applications on R as well. R for Data Science is the perfect book to pick up coding in R. It covers the concepts of data exploration, wrangling, programming, modelling, and communication. 

Understanding Machine Learning: From Theory to Algorithms – By Shai Shalev-Shwartz and Shai Ben-David

data science books - Understanding Machine Learning: From Theory to Algorithms

This is a great book for those who want a deeper understanding into machine learning concepts and algorithms. It covers the foundation of Machine Learning, algorithms in ML, additional learning models and advanced theory. This book provides a great reference for implementing machine learning algorithms yourself. An extensive theory behind algorithms helps enhance the understanding and application of the same. 

Data Science Books for Advanced Level

Deep Learning – By Ian Goodfellow, Yoshua Bengio, and Aaron Courville

This book is an amazing reference for deep learning algorithms. The book is not code-heavy but explains in-depth how to approach deep learning problems. The layout of the book is easy on the eyes with extensive use of bullets and images. Some of the topics covered in this book are introduction and explanation of the importance of deep learning; algorithms of backpropagation, convnets, recurrent neural nets; unsupervised deep learning; attention mechanisms and more.

Data Science Book for Data Mining

Mining of Massive Datasets – By Jure Leskovec, Anand Rajaraman, Jeff Ullman

This is an extremely comprehensive book developed on the basis of various Stanford courses on large scale data mining and network analysis. As the name suggests, it focusses on mining of very large datasets. One can learn to develop production-level models at a large scale with the help of this book. The major topics covered in this book are mining data streams, MapReduce, building recommendation systems, link analysis, dimensionality reduction, and more.

While self-study is an important aspect of learning new things and technologies, a structured approach with a certification course takes you a long way in your domain. If you wish to pursue a career in the field of data science, upskill with Great Learning’s PG program in Data Science and Business Analytics.   

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