For learning Data Science and R,
- Data Science from Scratch: First Principles of Python by Joel Grus
- Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing, and Presenting Data by John Wiley & Sons
- Data Science and big data analytics
- R for data science
To learn about Statistics,
- Head First Statistics: A Brain-Friendly Guide
- Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
- Practical Statistics for Data Scientists
- Naked Statistics: Stripping the Dread from Data by Charles Wheelan
For learning Probability, Machine learning, and Python,
- Introduction to Probability
- Introduction to Machine Learning with Python: A Guide for Data Scientists
- Python Machine Learning By Example
- Pattern recognition and machine learning
- Python for data analysis
- Python Data Science Handbook by Jake VanderPlas
- Business Analytics – A Data-Driven Decision-Making Approach for Business by Amar Sahay
There are hundreds of resources accessible to obtain a handle on the subject, including online courses, websites, videos, and books, although it may appear difficult at first. We’ll go through some of the greatest books for learning Data Science and associated technologies in this article, which will make learning a breeze.
Some of the best books in data science in 2021 are:
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Introduction to Machine Learning with Python: A Guide for Data Scientists by Author: Andreas C. Müller and Sarah Guido – This book covers a wide range of Machine Learning subjects in an approachable manner for novices, demonstrating how simple it is to get started developing their own Machine Learning solutions.
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R for Data Science by Author: Hadley Wickham, Garrett Grolemund – The book’s subjects include the fundamentals of Data Science, such as importing, cleaning, manipulating, visualizing, and modeling data using the R programming language.
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Naked Statistics by Author: Charles Wheelan – This book presents the key concepts of Data Science by tying them to real-world circumstances, making it an intriguing and humorous take on the subject.
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Practical Statistics for Data Scientists by Author: Andrew Bruce, Peter C. Bruce, and Peter Gedeck – This book is primarily geared for Data Science professionals who have prior knowledge of the programming language R and Statistics. It explains the subject’s main concepts in a user-friendly manner to aid learning.
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Python for Data Analysis by Author: Wes McKinney – It focuses on practical Python for Data Analysis implementations to analyze structured data saved in a variety of formats.
You can try our courses on data science to learn more