Free self-paced course

LLM Engineering Course

This hands-on LLM engineering course is for software developers building applications around language models. It covers typed model interfaces, retrieval and RAG, MCP tools, validation, evaluation, tracing, cost, latency, guardrails, and explicit failure recovery.

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For

Software developers who know Python, HTTP APIs, data structures, and automated testing.

Study time

24–36 hours

Prerequisites

Python, APIs, typed data, and basic LLM concepts. Start with LLM Foundations if needed.

What you will learn

  • Design validated model and tool interfaces.
  • Build hybrid retrieval and cited RAG.
  • Evaluate quality, failure, latency, and cost.
  • Ship a grounded assistant with operational controls.

Recommended starting guides

Use these answer-first lessons to build the concepts this course depends on.

Build a grounded RAG pipeline with citations and evaluationDesign safe Model Context Protocol tools and resourcesEngineer a reproducible AI agent harness

Course format

Each topic combines a concise explanation, an animated mechanism, hands-on evidence, and an optional book-level deep dive.

  • Code-first lessons
  • Structured outputs and MCP
  • RAG and retrieval evaluation
  • Security and observability
  • Grounded assistant capstone

Mastery evidence

Grounded AI Assistant

Build a cited assistant with fixed evaluations, abstention, guardrails, trace evidence, and a release gate.

Open the project

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