<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Data &amp; AI Engineering Tutorials on Data &amp; AI School</title><link>https://dataandaischool.io/</link><description>Recent content in Data &amp; AI Engineering Tutorials on Data &amp; AI School</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 20 Aug 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://dataandaischool.io/index.xml" rel="self" type="application/rss+xml"/><item><title>Getting an LLM to Follow the Rules: Reliable Structured Output</title><link>https://dataandaischool.io/ai-engineering/posts/reliable-structured-output/</link><pubDate>Thu, 20 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/reliable-structured-output/</guid><description>Why &amp;lsquo;just ask for JSON&amp;rsquo; isn&amp;rsquo;t enough, and the real techniques — schemas, function calling, output parsers — for getting consistent, parseable output every time.</description></item><item><title>Prompting Like a Pro (Not Like a Google Search)</title><link>https://dataandaischool.io/ai-engineering/posts/prompting-like-a-pro/</link><pubDate>Thu, 20 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/prompting-like-a-pro/</guid><description>The named prompt engineering patterns practitioners actually use — chain-of-thought, role prompting, and self-consistency — explained simply.</description></item><item><title>Stop Copy-Pasting Prompts: Building a Prompt Library That Scales</title><link>https://dataandaischool.io/ai-engineering/posts/prompt-templates-and-libraries/</link><pubDate>Thu, 20 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/prompt-templates-and-libraries/</guid><description>Moving from one-off prompts scattered in code to versioned, parameterized templates you can actually test, reuse, and maintain.</description></item><item><title>Evaluating GenAI Systems (Why 'It Feels Good' Isn't Enough)</title><link>https://dataandaischool.io/ai-engineering/posts/evaluating-genai-systems/</link><pubDate>Wed, 19 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/evaluating-genai-systems/</guid><description>GenAI systems need real evaluation — accuracy, relevance, safety — just like any other engineering system, not vibes-based judgment.</description></item><item><title>AI Agents 101: From Chatbot to Agent</title><link>https://dataandaischool.io/ai-engineering/posts/ai-agents-101/</link><pubDate>Tue, 18 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/ai-agents-101/</guid><description>The shift from a model that answers questions to one that takes real actions using tools — the plan, act, observe, repeat loop.</description></item><item><title>Hallucinations: Why They Happen and How to Reduce Them</title><link>https://dataandaischool.io/ai-engineering/posts/hallucinations-why-and-how-to-reduce/</link><pubDate>Mon, 17 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/hallucinations-why-and-how-to-reduce/</guid><description>The honest explanation for why LLMs make things up, and practical ways to reduce it — grounding, citations, and a few other levers.</description></item><item><title>The Modern Data Stack, Mapped Out</title><link>https://dataandaischool.io/data-engineering/posts/the-modern-data-stack-mapped-out/</link><pubDate>Mon, 10 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/data-engineering/posts/the-modern-data-stack-mapped-out/</guid><description>Everything you&amp;#39;ve learned, in one picture: how data sources, pipelines, storage, quality, modeling, and access all work together in 2026.</description></item><item><title>The Modern Data Stack, Mapped Out</title><link>https://dataandaischool.io/posts/the-modern-data-stack-mapped-out/</link><pubDate>Mon, 10 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/posts/the-modern-data-stack-mapped-out/</guid><description>Everything you&amp;#39;ve learned, in one picture — how data sources, pipelines, storage, quality, modeling, and access all work together in 2026.</description></item><item><title>Data Quality: What Can Actually Go Wrong</title><link>https://dataandaischool.io/data-engineering/posts/data-quality-what-can-actually-go-wrong/</link><pubDate>Sun, 09 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/data-engineering/posts/data-quality-what-can-actually-go-wrong/</guid><description>The silent failures that break dashboards and reports: why garbage data means garbage insights, and how to catch problems before they cascade.</description></item><item><title>Data Quality: What Can Actually Go Wrong</title><link>https://dataandaischool.io/posts/data-quality-what-can-actually-go-wrong/</link><pubDate>Sun, 09 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/posts/data-quality-what-can-actually-go-wrong/</guid><description>The silent failures that break dashboards and reports — why garbage data means garbage insights, and how to catch problems before they cascade.</description></item><item><title>What Is Data Modeling (and Why It Matters)</title><link>https://dataandaischool.io/data-engineering/posts/what-is-data-modeling-and-why-it-matters/</link><pubDate>Sat, 08 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/data-engineering/posts/what-is-data-modeling-and-why-it-matters/</guid><description>How to organize your data like a blueprint: designing warehouse structures so queries are fast, accurate, and make sense.</description></item><item><title>What Is Data Modeling (and Why It Matters)</title><link>https://dataandaischool.io/posts/what-is-data-modeling-and-why-it-matters/</link><pubDate>Sat, 08 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/posts/what-is-data-modeling-and-why-it-matters/</guid><description>How to organize your data like a blueprint — designing warehouse structures so queries are fast, accurate, and make sense.</description></item><item><title>Structured vs Semi-Structured vs Unstructured Data</title><link>https://dataandaischool.io/data-engineering/posts/structured-vs-semi-structured-vs-unstructured-data/</link><pubDate>Fri, 07 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/data-engineering/posts/structured-vs-semi-structured-vs-unstructured-data/</guid><description>Why some data fits neatly into tables and some doesn&amp;#39;t: why that difference shapes whether you use a warehouse or a lake.</description></item><item><title>Structured vs Semi-Structured vs Unstructured Data</title><link>https://dataandaischool.io/posts/structured-vs-semi-structured-vs-unstructured-data/</link><pubDate>Fri, 07 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/posts/structured-vs-semi-structured-vs-unstructured-data/</guid><description>Why some data fits neatly into tables and some doesn&amp;#39;t — and why that difference shapes whether you use a warehouse or a lake.</description></item><item><title>What Is a Data Pipeline, Really?</title><link>https://dataandaischool.io/data-engineering/posts/what-is-a-data-pipeline-really/</link><pubDate>Thu, 06 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/data-engineering/posts/what-is-a-data-pipeline-really/</guid><description>From raw data to insights: how a data pipeline connects every step and turns chaos into clarity.</description></item><item><title>What Is a Data Pipeline, Really?</title><link>https://dataandaischool.io/posts/what-is-a-data-pipeline-really/</link><pubDate>Thu, 06 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/posts/what-is-a-data-pipeline-really/</guid><description>From raw data to insights — how a data pipeline connects every step and turns chaos into clarity.</description></item><item><title>Batch vs Streaming Processing Explained Simply</title><link>https://dataandaischool.io/data-engineering/posts/batch-vs-streaming-processing-explained-simply/</link><pubDate>Wed, 05 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/data-engineering/posts/batch-vs-streaming-processing-explained-simply/</guid><description>Two ways to process data: all at once, or as it arrives, and why the difference shapes how data systems are built.</description></item><item><title>Batch vs Streaming Processing Explained Simply</title><link>https://dataandaischool.io/posts/batch-vs-streaming-processing-explained-simply/</link><pubDate>Wed, 05 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/posts/batch-vs-streaming-processing-explained-simply/</guid><description>Two ways to process data — all at once, or as it arrives — and why the difference shapes how data systems are built.</description></item><item><title>Embeddings and Vector Similarity</title><link>https://dataandaischool.io/ai-engineering/posts/embeddings-and-vector-similarity/</link><pubDate>Wed, 05 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/embeddings-and-vector-similarity/</guid><description>How text gets turned into numbers that capture meaning, and why &amp;lsquo;similar meaning = nearby numbers&amp;rsquo; is the foundation of search, recommendations, and RAG.</description></item><item><title>Data Warehouse vs Data Lake vs Lakehouse Explained Simply</title><link>https://dataandaischool.io/data-engineering/posts/data-warehouse-vs-data-lake-vs-lakehouse-explained-simply/</link><pubDate>Tue, 04 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/data-engineering/posts/data-warehouse-vs-data-lake-vs-lakehouse-explained-simply/</guid><description>Three places to store your data for analytics: what each one actually is, and why the difference matters.</description></item><item><title>Data Warehouse vs Data Lake vs Lakehouse Explained Simply</title><link>https://dataandaischool.io/posts/data-warehouse-vs-data-lake-vs-lakehouse-explained-simply/</link><pubDate>Tue, 04 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/posts/data-warehouse-vs-data-lake-vs-lakehouse-explained-simply/</guid><description>Three places to store your data for analytics — what each one actually is, and why the difference matters.</description></item><item><title>Prompting Fundamentals</title><link>https://dataandaischool.io/ai-engineering/posts/prompting-fundamentals/</link><pubDate>Tue, 04 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/prompting-fundamentals/</guid><description>Why specificity beats cleverness, and how to talk to a model that takes everything you say literally.</description></item><item><title>ELT vs ETL: What's the Difference?</title><link>https://dataandaischool.io/data-engineering/posts/elt-vs-etl-whats-the-difference/</link><pubDate>Mon, 03 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/data-engineering/posts/elt-vs-etl-whats-the-difference/</guid><description>Two ways to move data from source systems into a data warehouse, and why the order of operations matters.</description></item><item><title>ELT vs ETL: What's the Difference?</title><link>https://dataandaischool.io/posts/elt-vs-etl-whats-the-difference/</link><pubDate>Mon, 03 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/posts/elt-vs-etl-whats-the-difference/</guid><description>Two ways to move data from source systems into a data warehouse — and why the order of operations matters.</description></item><item><title>Tokens, Context Windows, and Why They Matter</title><link>https://dataandaischool.io/ai-engineering/posts/tokens-and-context-windows/</link><pubDate>Mon, 03 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/tokens-and-context-windows/</guid><description>What a token actually is, why every model has a memory limit, and why this quietly affects cost, speed, and what you can even ask a model to do.</description></item><item><title>How LLMs Actually Work (Next-Token Prediction, Simply Explained)</title><link>https://dataandaischool.io/ai-engineering/posts/how-llms-actually-work/</link><pubDate>Sun, 02 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/how-llms-actually-work/</guid><description>No math-heavy transformer internals, just the core idea: an LLM is a very sophisticated autocomplete engine trained on huge amounts of text.</description></item><item><title>OLTP vs OLAP Explained Simply</title><link>https://dataandaischool.io/data-engineering/posts/oltp-vs-olap-explained-simply/</link><pubDate>Sun, 02 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/data-engineering/posts/oltp-vs-olap-explained-simply/</guid><description>The two types of systems every data engineer works with: what they are, how they differ, and why the distinction matters.</description></item><item><title>OLTP vs OLAP Explained Simply</title><link>https://dataandaischool.io/posts/oltp-vs-olap-explained-simply/</link><pubDate>Sun, 02 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/posts/oltp-vs-olap-explained-simply/</guid><description>The two types of systems every data engineer works with — what they are, how they differ, and why the distinction matters.</description></item><item><title>What Is Data Engineering? A Simple Explanation for Beginners</title><link>https://dataandaischool.io/data-engineering/posts/what-is-data-engineering/</link><pubDate>Sat, 01 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/data-engineering/posts/what-is-data-engineering/</guid><description>A beginner-friendly explanation of what data engineers actually do, why the role exists, and how it&amp;#39;s different from data analysts and data scientists.</description></item><item><title>What Is Data Engineering? A Simple Explanation for Beginners</title><link>https://dataandaischool.io/posts/what-is-data-engineering/</link><pubDate>Sat, 01 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/posts/what-is-data-engineering/</guid><description>A beginner-friendly explanation of what data engineers actually do, why the role exists, and how it&amp;#39;s different from data analysts and data scientists.</description></item><item><title>What Is Generative AI (and What It Isn't)</title><link>https://dataandaischool.io/ai-engineering/posts/what-is-generative-ai/</link><pubDate>Sat, 01 Aug 2026 00:00:00 +0000</pubDate><guid>https://dataandaischool.io/ai-engineering/posts/what-is-generative-ai/</guid><description>The simple difference between predictive AI and generative AI, explained without the jargon.</description></item></channel></rss>