For developers & technical professionals
For developers who can ship an app but haven’t shipped anything with an LLM in it. RAG, agents, evals and production deployment — built live, on your own project, reviewed by a human.
8 weeks
1 live classes/week
Try 2 free classesIf the first two live classes of your first course don’t meet your expectations, we refund everything you paid. It only applies to your first Coderhouse course.
What will you learn in the AI Engineering course?
In this AI Engineering course you’ll learn to build, ship and operate real applications with LLMs, agents and automation, moving from “using AI” to “building with AI”.
You’ll start with the foundations of working with LLMs — tokens, context, model selection and your first API calls — and quickly move into prompting patterns, structured outputs and Retrieval-Augmented Generation (RAG) with embeddings and vector databases. Then you’ll build agents that use tools and orchestrate multi-step tasks, and speed up your work with AI-assisted development using Cursor and Claude Code.
The program closes with evaluation, safety and cost optimization, and a capstone where you design, build and deploy a production-style AI application or agent — a portfolio piece you’ll present on demo day.
Who it’s for
Developers who want to build, ship and operate real applications with LLMs, agents and automation.
Technical professionals with basic programming familiarity (Python helps) ready to move from using AI to building with AI.
Professionals who want to deploy a production-style AI application and add a portfolio piece with a live demo.
Tools you’ll use
LLM APIs
Vector databases
AI agents
Cursor
Claude Code
When you finish
Design and build AI agents that use tools, orchestrate multi-step tasks and connect to real systems.
Implement Retrieval-Augmented Generation (RAG) with embeddings and vector databases to build knowledge assistants.
Accelerate development with Cursor, Claude Code and prompt-to-production workflows.
Eight weeks, live
2 weekly live online classes of 2 h. 6 to 8 hours per week.
Week 1
Foundations of building with LLMs
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How LLMs work in practice: tokens and context
Model selection and trade-offs
Your first API calls
Pre-delivery 1: First working LLM integration
Live Session: Foundations of Building with LLMs
Week 2
Prompting & structured outputs
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Week 3
Retrieval-Augmented Generation (RAG)
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Week 4
Agents & tool use
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Week 5
AI-assisted development
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Week 6
Workflow automation
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Week 7
Evaluation, safety & cost
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Week 8
Capstone
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October 14
$495 launch price. Two free classes first.
FAQ
How do the two free classes work?
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Is the AI teaching the course?
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How much time does it take per week?
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Do I need experience to join?
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What if I can’t make a live class?
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When do cohorts start, and when does enrollment close?
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