You read the book.
Now put it to work.
Every practice dataset, template and guide from the book is ready for you here.
The library is free. Share your email and I’ll open it up.
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Get the Data Science For Dummies Reader Toolkit
Enter your email and I’ll open up the resource library that goes with the book.
- The 12 practice datasets from the walkthroughs, so you can follow along instead of reading along
- The Analytics Project Custom Instructions from Chapter 5, ready to upload to your own ChatGPT Project
- The Selling To Stakeholders Formula and Executive Relationship Management Planner from Chapter 12
- The stakeholder communication best practices and email template from Chapter 13
- The done-for-you Channel Scorecard Calculator from Chapter 15
- Curated tool, course and community recommendations from Chapter 21
You’re in.
Your Reader Resource Library is open. Every file lives on the site, chapter by chapter.
Open the Reader Resource Library →Nothing to wait for and nothing to download twice — the library is a permanent page you can bookmark.
Welcome back.
Open your Reader Resources →
Everything you need to turn the book into action
The book shows you the method. These are the files that let you run that method on your own data this week.
Go deeper by chapter
If you came here from a specific chapter, start here. Each chapter has its own resources. The resources you need are listed under that chapter.
Part 1 Getting Started with Data Science in the Age of AI
Chapter 1: Doing Data Science in an AI World
Chapter 2: Understanding Data and Thinking Like an Analyst
Covered in the book. No separate download for this chapter.
Chapter 3: Getting and Cleaning Data without Coding
Covered in the book. No separate download for this chapter.
Chapter 4: AI Tool Literacy – When to Trust, When to Verify
Covered in the book. No separate download for this chapter.
Part 2 Extracting Insights without Code
Chapter 5: Prompt Engineering for Analytics
Chapter 6: Exploring Your Data with AI
Chapter 7: Building Machine Learning Models without Code
Chapter 8: Understanding Essential Math and Statistics
Chapter 9: Clustering and Segmentation with AI
Chapter 10: Getting Predictive Analytics with Regression Analysis
Chapter 11: Building Dashboards with AI
Chapter 12: Data Storytelling and Visualization in the Age of AI
Part 3 Driving Business Value with AI and Analytics
Chapter 13: Developing Your Business Acumen
Chapter 14: Improving Operations with Data and AI
Chapter 15: Making Marketing Improvements with AI
Chapter 16: Decision Support and BI Copilots
Chapter 17: Risk and Fraud Detection with AI
Part 4 Implementing Data Science in Your Organization
Chapter 18: Gathering Important Information about Your Company
Covered in the book. No separate download for this chapter.
Chapter 19: Narrowing In on the Optimal Data Science Use Case
Covered in the book. No separate download for this chapter.
Chapter 20: Planning for Future Data Science Project Success
Covered in the book. No separate download for this chapter.
Chapter 21: Becoming an AI-Driven Data Professional
Part 5 The Part of Tens
Chapter 22: Ten Prompts Every Analytics Power User Should Master
Covered in the book. No separate download for this chapter.
Chapter 23: Ten Reliable AI and Data Science Tools
Covered in the book. No separate download for this chapter.
Want to keep going?
I write about what’s actually working in data and AI right now: the tools I’m using in client work, the workflows that hold up under pressure, and the workflows that quietly fall apart. The Convergence newsletter has the same practical, show-me-how tone as the book. It arrives while the information is still current. Reader Toolkit members get it automatically, so you don’t need to sign up twice.
Want help applying the book’s method?
Some of you are reading this book because a decision is waiting for you once you finish it. If that’s you, here are three ways I work with people.
Advisory and Fractional CMO
For founders and executives who need senior direction on data-driven growth without hiring a full-time CMO.
Fractional CMO servicesTeam Training and Workshops
For teams who want their analysts, marketers and operators to work the way this book describes, quickly and as one team.
Ask about training and workshopsSpeaking
For conferences and internal events. I’ve spoken in 16 cities across 10 countries, for organizations including IBM, Ericsson and National Geographic.
Ask about speaking
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About the author
I’m Lillian Pierson. I’ve spent my career building data-driven growth solutions for companies including IBM, Intel, Dell and SAP, which is where the messy, real datasets in the practice files came from. The Chapter 4 verification tools exist because I needed them on those projects before I ever wrote them down.
12 books with Wiley · 2M+ people taught · Licensed Professional Engineer
More about me →
Keep the book working after the last page.
Take the prompts, the datasets and the frameworks with you, and get the new material as I release it.
Get the Data Science For Dummies Reader Toolkit
Enter your email and I’ll open up the resource library that goes with the book.
- The 12 practice datasets from the walkthroughs, so you can follow along instead of reading along
- The Analytics Project Custom Instructions from Chapter 5, ready to upload to your own ChatGPT Project
- The Selling To Stakeholders Formula and Executive Relationship Management Planner from Chapter 12
- The stakeholder communication best practices and email template from Chapter 13
- The done-for-you Channel Scorecard Calculator from Chapter 15
- Curated tool, course and community recommendations from Chapter 21
You’re in.
Your Reader Resource Library is open. Every file lives on the site, chapter by chapter.
Open the Reader Resource Library →Nothing to wait for and nothing to download twice — the library is a permanent page you can bookmark.