Foundations of Data Science with Python

The book Foundations of Data Science with Python provides an introduction to data science, covering topics such as data manipulation, visualization, probability, statistics, and dimensionality reduction. It uses a computational-first approach and teaches readers how to use Python and data-science libraries to perform statistical tests using real data sets. The book is targeted toward engineers and scientists, but is also accessible to anyone with basic calculus and computer programming knowledge. It offers a modern, computational approach to working with data and includes an accompanying website with interactive tools to help the reader learn the material.

Format: Paperback / softback
Length: 496 pages
Publication date: 22 February 2024
Publisher: Taylor & Francis Ltd

Introduction:

The Foundations of Data Science with Python is a comprehensive guide that introduces readers to the fundamental principles and techniques of data science. This book is designed for engineers and scientists, but its content is accessible to anyone with a basic understanding of calculus and computer programming. The book adopts a computational-first approach to data science, emphasizing the use of Python and the associated data science libraries to visualize, transform, and model data. It also teaches readers how to conduct statistical tests using real data sets, employing a simple and general approach known as resampling.

Key Features:

1. Modern, Computational Approach: The book takes a modern, computational approach to data science, emphasizing the use of Python and its powerful libraries. It teaches readers how to efficiently handle large datasets and perform complex data analysis tasks.
2. Real Data Sets: The book utilizes real data sets to conduct statistical tests that address a diverse range of contemporary issues. These issues include the effects of socioeconomic factors on the spread of the COVID-19 virus, the impact of state laws on firearms mortality, and more. By using real data, readers can gain a deeper understanding of the practical applications of data science.
3. Comprehensive Coverage: The book covers a wide range of topics in data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. It provides a solid foundation for those who want to pursue further studies in data science or apply their knowledge in real-world scenarios.
4. Accessible to Practicing Engineers and Scientists: Despite its focus on technical concepts, the book is written in a clear and concise manner that is accessible to practicing engineers and scientists who need to gain foundational knowledge of data science. It includes numerous examples and exercises to help readers apply the concepts learned in the book.

Conclusion:

The Foundations of Data Science with Python is an essential resource for anyone interested in data science, engineering, or science. It provides a comprehensive and up-to-date introduction to the field, covering a wide range of topics and employing a computational-first approach. With its real data sets and practical applications, this book is sure to be valuable to students, professionals, and researchers alike.

Weight: 1056g
Dimension: 179 x 255 x 33 (mm)
ISBN-13: 9781032350424