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    Learn AI Data Engineering in a Month of Lunches (MEAP 01)

    Posted By: DexterDL
    Learn AI Data Engineering in a Month of Lunches (MEAP 01)

    Learn AI Data Engineering in a Month of Lunches (MEAP 01)
    English | 2025 | ISBN: 9781633435728 | 134 pages | PDF,EPUB | 7.74 MB


    Reliable and effective AI-powered data pipelines delivered in just a month of lunches!

    Learn AI Data Engineering in a Month of Lunches is a fast, friendly guide to integrating large language models into your data workflows. In just 17 short lessons, 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!

    In Learn AI Data Engineering in a Month of Lunches 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 to automate code, 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

    Learn AI Data Engineering in a Month of Lunches 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.
    about the book
    Learn AI Data Engineering in a Month of Lunches 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 designed to fit into a lunch break, you’ll learn just enough theory to understand the why, and then immediately put it into practice.