ManningBooks

ManningBooks

Devtalk Sponsor

Learn AI Data Engineering in a Month of Lunches (Manning)

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!

David Melillo

This book shows you how to integrate large language models (LLMs) and AI into your everyday data engineering workflows. It’s built on short, hands-on lessons that are designed to fit into a lunch break, so you don’t need to dedicate long blocks of time to upskill.

Here are some of the things you’ll learn:

  • How to craft better prompts for AI to help with SQL and Python tasks like data cleaning, transformations, etc.

  • Ways to use ChatGPT (or similar) to write, debug, and optimize your data code.

  • Embedding AI into pipelines via APIs to automate repetitive tasks

  • Working with messy, real-world data and extracting insights.

  • Building “agentic workflows” (i.e. more autonomous components) to scale the expertise in your org.


:busts_in_silhouette: Who it’s for

  • Data engineers & architects who already know SQL & Python.

  • Data professionals who want to boost productivity, especially on the tedious parts of pipelines.

  • Folks curious about using LLMs beyond “just chatbots” — actually integrating them into production pipelines.


:magnifying_glass_tilted_left: Why this might matter to you

Here are a few reasons I think this book could be a useful addition to your toolbox:

  • “Lunch break scale.” The format means you can digest something new each day without carving out a full weekend. Great for steady progress.

  • Tool-chain relevance. There’s a gap today: many engineers want to use AI for helping with the hairy bits (dirty data, edge cases, debugging), but the path isn’t always clear. This book seems to aim directly at that gap.

  • Future-proofing. As more parts of data architecture get “augmented” by AI, knowing how to embed those tools well, cleanly, and with performance in mind is going to be a differentiator.


:warning: Things to watch out for

  • Since AI & LLMs are moving fast, some tools/versions may evolve. Expect some parts to date quicker than more theory/architecture bits.

  • Real-world constraints (cost, latency, security, governance) often complicate AI in pipelines. The “lunch-lesson” format is great, but applying at scale means needing to think about infra, error handling, monitoring, etc. Make sure you test in your domain.

  • If you’re brand new to data engineering (SQL & Python basics, ETL/ELT patterns), you may need supplemental learning — this isn’t a beginner’s “intro to data engineering” book; it assumes some knowledge already.


Don’t forget you can get 45% off with your Devtalk discount! Just use the coupon code “devtalk.com” at checkout :+1:

Most Liked

DevotionGeo

DevotionGeo

Manning’s Learn in a Month of Lunches series is excellent.

DevotionGeo

DevotionGeo

You’re welcome! Keep up the great work.

ManningBooks

ManningBooks

Devtalk Sponsor

Thank you.

Where Next?

Popular Ai topics Top

ManningBooks
Before deploying an AI model into production, you need to know more than just its accuracy. Will it be fast enough for your users? Will i...
New
ManningBooks
In Build a Reasoning Model (From Scratch), acclaimed ML research engineer Sebastian Raschka takes you inside the black box of reasoning-e...
New
ManningBooks
Based on Ilya Sutskever’s famous “must-read” list of ~30 AI papers, this book walks you through the research that shaped today’s deep lea...
New
ManningBooks
Learn AI Data Engineering in a Month of Lunches is a fast, friendly guide to integrating large language models into your data workflows. ...
New
New
ManningBooks
Build an AI Agent (From Scratch) is a step-by-step guide to creating a working AI agent, starting with the bare essentials and growing yo...
New
ManningBooks
Grokking AI Algorithms, Second Edition introduces the most important AI algorithms using relatable illustrations, interesting examples, a...
New
ManningBooks
The bestselling book on Python deep learning, now covering generative AI, Keras 3, PyTorch, and JAX! François Chollet and Matthew ...
New
pragdave
Build robust LLM-powered apps, chatbots, and agents while mastering AI engineering principles that will help you outlast the tools and th...
New
ManningBooks
Erlang and OTP in Action teaches you the concepts of concurrent programming and the use of Erlang’s message-passing model. It walks you t...
New

Other popular topics Top

Devtalk
Reading something? Working on something? Planning something? Changing jobs even!? If you’re up for sharing, please let us know what you’...
1040 20280 387
New
AstonJ
Just done a fresh install of macOS Big Sur and on installing Erlang I am getting: asdf install erlang 23.1.2 Configure failed. checking ...
New
PragmaticBookshelf
Build highly interactive applications without ever leaving Elixir, the way the experts do. Let LiveView take care of performance, scalabi...
New
PragmaticBookshelf
Build efficient applications that exploit the unique benefits of a pure functional language, learning from an engineer who uses Haskell t...
New
husaindevelop
Inside our android webview app, we are trying to paste the copied content from another app eg (notes) using navigator.clipboard.readtext ...
New
New
New
PragmaticBookshelf
Develop, deploy, and debug BEAM applications using BEAMOps: a new paradigm that focuses on scalability, fault tolerance, and owning each ...
New
AstonJ
Curious what kind of results others are getting, I think actually prefer the 7B model to the 32B model, not only is it faster but the qua...
New
mindriot
Ok, well here are some thoughts and opinions on some of the ergonomic keyboards I have, I guess like mini review of each that I use enoug...
New