'Dr. Chirag Shah's A Hands-On Introduction to Data Science with R is an essential addition to any aspiring or practicing data scientist's library. He masterfully breaks down complex quantitative ideas into clear, digestible explanations, hitting the perfect balance of detail without being overwhelming. What truly sets this book apart are the practical R exercises. They are seamlessly woven into the text, transforming abstract concepts into tangible skills. This isn't just a book you read; it's a book you do. It delivers on its promise of a hands-on introduction, making it an invaluable resource for students taking their first steps and professionals looking for a practical refresher.' Bhupesh Shetty, Drexel University

'This updated text again strikes the perfect balance between theory and practice. I appreciate how it offers two distinct editions, allowing readers to choose Python or R as their programming language. The examples feel fresh, the code is practical, and the explanations connect beautifully with real-world data work.' Zhen Zhu, University of Kent

Praise for the first edition: 'Dr. Shah has written a fabulous introduction to data science for a broad audience. His book offers many learning opportunities, including explanations of core principles, thought-provoking conceptual questions, and hands-on examples and exercises. It will help readers gain proficiency in this important area and quickly start deriving insights from data.' Ryen W. White, Microsoft Research AI

Students will develop a practical understanding of data science with this hands-on textbook for introductory courses. This new edition is fully revised and updated, with numerous exercises and examples in the popular data science tool R, a new chapter on using R for statistical analysis, and a new chapter that demonstrates how to use R within a range of cloud platforms. The many practice examples, drawn from real-life applications, range from small to big data and come to life in a new end-to-end project in Chapter 11. New 'Data Science in Practice' boxes highlight how concepts introduced work within an industry context and many chapters include new sections on AI and Generative AI. A suite of online material for instructors provides a strong supplement to the book, including lecture slides, solutions, additional assessment material and curriculum suggestions. Datasets and code are available for students online. This entry-level textbook is ideal for readers from a range of disciplines wishing to build a practical, working knowledge of data science.
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Part I. Conceptual Introductions: 1. Introduction; 2. Data; Part II. Tools for Data Science: 3. Techniques; 4. Introduction to R; 5. R for Statistical Analysis; 6. Cloud Computing; Part III. Machine Learning for Data Science: 7. Machine Learning Introduction and Regression; 8. Supervised Learning; 9. Unsupervised Learning; Part IV. Applications, Evaluations, and Methods: 10. Data Collection, Experimentation, and Evaluation; 11. Hands-On with Solving Data Problems.
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A hands-on textbook for introductory data science courses that use R.

Produktdetaljer

ISBN
9781009589079
Publisert
2026-01-22
Utgave
2. utgave
Utgiver
Cambridge University Press
Vekt
1132 gr
Aldersnivå
U, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
406

Forfatter

Biografisk notat

Chirag Shah is Professor of Information and Computer Science at University of Washington (UW) in Seattle. He is the Founding Director for InfoSeeking Lab and Founding Co-Director of the Center for Responsibility in AI Systems & Experiences (RAISE). His research focuses on building, auditing, and correcting intelligent information access systems. Dr. Shah is a Distinguished Member of ACM as well as ASIS&T, and a Senior Member of IEEE. He has published nearly 200 peer-reviewed articles and authored several books, including textbooks on data science and machine learning. He regularly engages with industrial research labs at Amazon, ByteDance, Microsoft Research, and Spotify.