Get the eBook free when you register your print book at Manning. This book is a fast, friendly guide to integrating large language models into your data workflows. You'll learn how AI can help you handle time-consuming data engineering tasks including transformations, calculations, and the never-ending chore of data cleaning-all illustrated with instantly-familiar SQL and Python use cases! This book shows you far more than copy-pasting prompts or using AI as a coding assistant. You'll learn how to integrate LLMs at an API level to give a real performance and efficiency boost to your pipelines. Each chapter contains a new relevant technique to automate transformations, enrich datasets, and accelerate tedious workflows with AI. In Learn AI Data Engineering you'll learn how to: * Craft smarter prompts to get the best results from LLMs on data tasks * Use ChatGPT to write, debug, and optimize SQL and Python faster * Embed AI directly into pipelines for code automation, analysis, and enrichment * Clean, transform, and extract insights from real-world messy data with AI * Build agentic workflows that capture and scale subject matter expertise About the book Learn AI Data Engineering teaches you to apply AI to the most important data engineering tasks. You'll build a portfolio of hands-on projects, like querying the Pagila DVD rental database with ChatGPT, performing real-time sentiment analysis on news headlines, and even prototyping agentic workflows that simulate real business rules. With each lesson you'll learn just enough theory to understand the why, and then immediately put it into practice.
About the reader For aspiring and veteran data professionals who know Python and SQL. About the author Dave Melillo is a data leader with deep expertise across data analytics, data engineering, data architecture, and data science and machine learning. He has built large-scale data products, architected modern pipelines, and trained professionals at universities and Fortune 500 companies. His writing on practical data strategies has been featured in Towards Data Science and Dev Genius.