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Data Science For Dummies de Lillian Pierson

Data Science For Dummies: For Dummies

Autor Lillian Pierson
en Limba Engleză Paperback – 10 sep 2026

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Specificații

ISBN-13: 9781394424085
ISBN-10: 1394424086
Pagini: 432
Dimensiuni: 188 x 233 x 27 mm
Greutate: 0.59 kg
Ediția:4. Auflage
Editura: Wiley
Seria For Dummies

Notă biografică

Lillian Pierson, PE, is an AI-native growth strategist, advisor, and fractional CMO who helps B2B technology companies modernize their go-to-market strategies and systems. A licensed professional engineer, AI author, and educator, she combines deep technical expertise with growth leadership to help companies scale demand, strengthen competitive positioning, and drive revenue growth. She has written more than a dozen books on AI and data science, supported 10% of Fortune 100 companies, and educated more than two million learners worldwide.

Cuprins

Introduction 1
Part 1: Getting Started with Data Science in the Age of AI 7
CHAPTER 1: Doing Data Science in an AI World 9
CHAPTER 2: Understanding Data and Thinking Like an Analyst 23
CHAPTER 3: Getting and Cleaning Data without Coding 39
CHAPTER 4: AI Tool Literacy - When to Trust, When to Verify 59
Part 2: Extracting Insights without Code 75
CHAPTER 5: Prompt Engineering for Analytics 77
CHAPTER 6: Exploring Your Data with AI 99
CHAPTER 7: Building Machine Learning Models without Code 117
CHAPTER 8: Understanding Essential Math and Statistics 137
CHAPTER 9: Clustering and Segmentation with AI 157
CHAPTER 10: Getting Predictive Analytics with Regression Analysis 173
CHAPTER 11: Building Dashboards with AI 193
CHAPTER 12: Data Storytelling and Visualization in the Age of AI 213
Part 3: Driving Business Value with AI and Analytics 235
CHAPTER 13: Developing Your Business Acumen 237
CHAPTER 14: Improving Operations with Data and AI 251
CHAPTER 15: Making Marketing Improvements with AI 265
CHAPTER 16: Decision Support and BI Copilots 283
CHAPTER 17: Risk and Fraud Detection with AI 299
Part 4: Implementing Data Science in Your Organization 311
CHAPTER 18: Gathering Important Information about Your Company 313
CHAPTER 19: Narrowing In on the Optimal Data Science Use Case 333
CHAPTER 20: Planning for Future Data Science Project Success 349
CHAPTER 21: Becoming an AI-Driven Data Professional 363
Part 5: The Part of Tens 381
CHAPTER 22: Ten Prompts Every Analytics Power User Should Master 383
CHAPTER 23: Ten Reliable AI and Data Science Tools 393
Index 401