Also posted as LLM Engineer · GenAI Engineer · Applied AI Engineer · AI Agent Engineer · Agentic AI Engineer
Ships LLM features and agents into a product and keeps them working after launch.
What a hiring manager expects an AI Engineer to know, mapped to our courses in the order to learn them. You start with how models behave, build an agent with tools and connect it to real systems, then prove it works, run it in production and keep its cost predictable. Every requirement on this path has a course.
8 courses60 lessons~166 hours
What the job needs
Solid: course readyDashed: coming soon
Every requirement on this path has a course. Nothing to wait for.
8
Courses
0
Coming soon
~166
Hours
Every course on this path assumes you can write Python or TypeScript and work in a terminal. These foundations aren't written yet, so they sit outside the course count. Tick what you already know.
5 to learn · ~44h · 0 known
Syntax, packages with uv, reading API responses and the parts of the standard library you'll actually use.
Planned~12hUsed by 2 courses
Types, async and await, npm, and running a Node 24 project from the terminal.
Planned~12hUsed by 5 courses
Shell basics, branches, pull requests and the commands Claude Code runs on your behalf.
Planned~6hUsed by 7 courses
Methods, status codes, headers, JSON and calling a model provider with an API key.
Planned~6hUsed by 2 courses
Tables, joins, indexes and the schema design the memory and infrastructure courses build on.
Planned~8hUsed by 1 course
Learned these elsewhere? The setup guides get Claude Code, Python with uv and Node with TypeScript running in about an hour, so you can start course one today.
Setup guidesEach requirement is covered by a course, placed after the ones it builds on. Overviews are open to everyone; sign in to start the lessons.
How large language models are built, trained and run, so you can reason about their behaviour, cost and failure modes in production.
3 modules · 9 lessons ~18h 9 quizzes Capstone
Modules
Capstone: Choose a model for document extraction
What an AI agent really is, how it uses tools and context, and how to make one dependable enough for high-stakes work.
2 modules · 6 lessons ~18h 6 quizzes Capstone
Modules
Capstone: A document review agent in Claude Code
Build real agents on production harnesses: Claude Code, the Claude Agent SDK and Vercel's eve, with skills, subagents and human approval built in.
2 modules · 6 lessons ~20h 6 quizzes Capstone
Modules
Capstone: A drafting agent with human approval in eve
Design, build and ship Model Context Protocol servers that agents use well, and see how MCP's mental model differs from REST.
3 modules · 8 lessons ~26h 8 quizzes Capstone
Modules
Capstone: Ship an MCP server for an existing REST API
Turn "it seems better" into numbers you can defend: error analysis, code graders, calibrated LLM judges and honest statistics.
2 modules · 7 lessons ~20h 7 quizzes Capstone
Modules
Capstone: A full eval suite for your drafting agent
Ask a question, design the experiment, annotate the data, doubt the result, write it up and get it reviewed: the research discipline for AI agent work.
3 modules · 10 lessons ~26h 10 quizzes Capstone coming soon
Modules
Capstone: A small study on the triage agent (coming soon)
Take an agent from working demo to a system you can run for months: architecture, security, compliance, observability and safe change.
2 modules · 6 lessons ~18h 6 quizzes Capstone
Modules
Capstone: Production-readiness review and hardening
Know what each case costs in tokens, then cut that cost with caching, trimming, batching, routing, distillation and self-hosting, without losing quality.
2 modules · 8 lessons ~20h 8 quizzes Capstone
Modules
Capstone: Cost-engineer an agent pipeline
This path is what the role asks for, mapped to the courses we have. A requirement we haven't written the course for yet stays on the path as coming soon, so you can see the whole job, not just the part we cover.
