Book contents
- A Hands-On Introduction to Data Science
- A Hands-On Introduction to Data Science
- Copyright page
- Contents
- Preface
- About the Author
- Part I Conceptual Introductions
- 1 Introduction
- 2 Data
- 3 Techniques
- Part II Tools for Data Science
- Part III Machine Learning for Data Science
- Part IV Applications, Evaluations, and Methods
- Book part
- Index
1 - Introduction
from Part I - Conceptual Introductions
Published online by Cambridge University Press: 07 February 2026
Book contents
- A Hands-On Introduction to Data Science
- A Hands-On Introduction to Data Science
- Copyright page
- Contents
- Preface
- About the Author
- Part I Conceptual Introductions
- 1 Introduction
- 2 Data
- 3 Techniques
- Part II Tools for Data Science
- Part III Machine Learning for Data Science
- Part IV Applications, Evaluations, and Methods
- Book part
- Index
Summary
This introductory chapter defines data science as a field focused on collecting, storing, and processing data to derive meaningful insights for decision-making. It explores data science applications across diverse sectors including finance, healthcare, politics, public policy, urban planning, education, and libraries. The chapter examines how data science relates to statistics, computer science, engineering, business analytics, and information science, while introducing computational thinking as a fundamental skill. It discusses the explosive growth of data (the 3Vs: velocity, volume, variety) and essential skills for data scientists, including statistical knowledge, programming abilities, and data literacy. The chapter concludes by addressing critical ethical concerns around privacy, bias, and fairness in data science practice.
Keywords
Information
- Type
- Chapter
- Information
- A Hands-On Introduction to Data Science with Python , pp. 3 - 42Publisher: Cambridge University PressPrint publication year: 2026
Accessibility standard: Inaccessible, or known limited accessibility
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