A Hands-On Introduction to Data Science with Python
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
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Product details:
- Edition number 2
- Publisher Cambridge University Press
- Date of Publication 22 January 2026
- ISBN 9781009588942
- Binding Paperback
- No. of pages424 pages
- Size 254x203x22 mm
- Weight 1012 g
- Language English 697
Categories
Short description:
A hands-on textbook for introductory data science courses that use Python.
MoreLong description:
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 Python, a new chapter on using Python for statistical analysis, and a new chapter that demonstrates how to use Python 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.
MoreTable of Contents:
Part I. Conceptual Introductions: 1. Introduction; 2. Data; Part II. Tools for Data Science: 3. Techniques; 4. Python; 5. Python 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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