Computational and Inferential Thinking: The Foundations of Data Science is a comprehensive book that introduces readers to the essential concepts and skills required for data science. The book aims to provide a foundational understanding of how to think computationally and inferentially about data, as well as the tools and techniques necessary for processing and analyzing it.

The book is written by Ani Adhikari and John DeNero, both professors of statistics and computer science at the University of California, Berkeley. Their combined expertise in these fields makes for a highly informative and engaging read.

The book starts by introducing readers to the basics of programming in Python, a popular language used extensively in data science. Readers will learn how to write simple programs and gradually progress to more advanced topics, such as object-oriented programming and debugging.

Next, the authors delve into the core principles of statistics, including probability, statistical inference, and hypothesis testing. They provide a detailed explanation of how to use these concepts to analyze data and draw meaningful conclusions from it.

The book also covers the foundational ideas of machine learning, including supervised and unsupervised learning, as well as deep learning. The authors provide readers with a practical guide to building and evaluating machine learning models, including methods for handling large datasets and selecting appropriate algorithms.

One of the unique features of this book is its focus on computational thinking, which refers to the ability to break down complex problems into smaller, more manageable components that can be solved with programming. The authors provide readers with a range of exercises and case studies that help to develop these skills.

The book is suitable for readers with little to no prior experience in programming or statistics, making it an ideal resource for students, academics, and professionals looking to develop their data science skills. The clear and concise explanations, combined with numerous examples and exercises, make it an engaging and accessible read.

Overall, Computational and Inferential Thinking: The Foundations of Data Science is a must-read for anyone looking to gain a comprehensive understanding of the fundamentals of data science. The authors’ expertise and engaging writing style make it an informative and enjoyable read that will undoubtedly leave readers with a solid foundation in this exciting and rapidly evolving field.