From Data to Impact

From Data to Impact

A structured, project-based path from Python fundamentals to production-ready data science, with the engineering discipline to make it matter.

By Anthony Faustine    

10 Parts

20+ Chapters

3 Parts complete

Start learning Read the preface

NoteHow this book works

Every chapter is a Jupyter notebook or QMD file meant to be run top to bottom, not just read. Along the way you will see four recurring markers:

Marker	Purpose
Key Concept	The core idea, precisely defined
Activity	Hands-on challenge: fill in the ... yourself before moving on
Common Mistake	A bug pattern worth recognising on sight
Pro Tip	A production-grade habit

Your learning path

Act 1  ·  Build the Foundation

Language, data wrangling, and engineering practices

• 01Foundations
• 02Data Analysis
• 03Dev Tools

Act 2  ·  Master the Models

Classical ML, deep learning, and large language models

• 04Classical MLsoon
• 05Deep Learningsoon
• 06LLMssoon

Act 3  ·  Ship to Production

MLOps pipelines, CI/CD, and production monitoring

• 07MLOpssoon
• 08Production Monitoringsoon

Act 4  ·  Design for Impact

Scalable ML systems and value-driven AI

• 09ML System Designsoon
• 10Value-driven AIsoon

Parts are released chapter by chapter as each reaches the same standard as Acts 1–3.  View source on GitHub