Organizations' heavy reliance on data for decision-making serves as sufficient evidence of the value of data. Who wouldn't want to be a part of a sector that is so promising when everyone is aware that data is the most important factor in helping any organization reach its goals? This eventually sheds information on the level of demand for data science as a profession. Moreover, data scientists are in more demand, which signifies that you need to be well-versed in the subject. Apart from books, there are several Data science coursesyou can look into. 

Some of the popular data science books are: 

•  Practical statistics for data scientists – By Peter Bruce and Andrew Bruce

Since it starts from scratch and covers a wide range of topics, including randomization, distribution, sampling, etc., this book is a unique joy for novices. The language is quite simple to comprehend. As a result, even a complete beginner can benefit from this book.

•  Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing, and Presenting Data

This book from John Wiley & Sons discusses many of the techniques, tools, and activities used by data scientists. You would be able to use open-source software to recreate with the aid of examples. This book has it all: concepts, principles, and real-world applications.

•  Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville

This book is for you if you want to learn about data-driven machine learning and deep learning in the data science sector. This book will guide you through everything, from the basic practical aspects of data science to machine learning applications.

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

Data science includes machine learning as a critical component. In light of this, Andreas C. Müller and Sarah Guido created this fantastic manual. Beginners will benefit from this book's explanations of the fundamentals of machine learning and Python.

•  R for Data Science

It's crucial for data scientists to be proficient in R. The book "R for Data Science" comes in handy in this situation. Data wrangling, programming, data exploration, data modeling, and communication are just a few of the many subjects covered in this book.

•  Python for Data Analysis – By Wes McKinney

Python is a well-liked programming language in data science, just like R. Because of this, "Python for Data Analysis" offers a full introduction to Python for those who want to grasp the fundamentals of data analytics. You can create practical applications with the aid of this book.

I sincerely hope that these recommendations of data science books have provided you with the self-assurance to upskill yourself. If you’re starting your career from scratch or want to enhance your skills, Learnbay offers a comprehensive data science course in Chennai for working professionals. Enroll today and prepare to transform your career.