For engineers with 5+ years shipping production code · Application only

Break into AI engineering — with a coach, not a course.

The AI Engineering Program takes senior software engineers from LLM fundamentals to a deployed, production-grade portfolio and a high-paying AI role. Six months. Seven production builds. 4–6 hours a week.

Kirill Eremenko

Built and taught by Kirill Eremenko — founder of SuperDataScience,
3M+ students taught.

Our graduates work at
Google
Amazon
Meta
NASA
Scale AI
ServiceNow
Adobe
Expedia
Deloitte
Intel

Software engineer → what's your next move?

These roles are within reach of the code you already write.

Median US total compensation, 2026 — levels.fyi, Perspective AI. Don't take our word for it — look it up.

Software Engineer$130k
AI Engineer$244k
Senior AI Engineer$320k
Forward Deployed Engineer$385k
Frontier labs$600k+

What it actually is

Everything you need to judge this before you talk to anyone.

Format
A coached program, not a course library. A skill-gap audit and a personalized roadmap, a dedicated coach who reviews your work each week, unlimited 1-on-1 calls, private Slack, live office hours four times a week, and a small peer group of engineers at your level.
Length
A 12-week core curriculum, then 14 more weeks of support until you land the role. Six months.
Time
4–6 hours a week. About 45 minutes a day. Built for people with a job, a mortgage and kids.
What you build
Seven production systems — a deployed RAG chatbot of yourself, a multi-agent researcher-writer, a multi-MCP agent, a full-stack AI product, two AWS deployments, and a capstone scoped to your target role.
What you learn
Raw Python first: LLM APIs, context, memory, tool calling, RAG, embeddings, vector databases. Then agents, MCP and frameworks. Then production on AWS — evals, CI/CD, observability, guardrails, cost.
Who teaches
Practitioners who ship production AI, plus a career coach with 12 years recruiting at Google.
You leave with
A public portfolio of deployed systems, real consulting experience on your CV, the AWS AI Practitioner certification, and a job-search strategy built around your background.
Entry
Application and a strategy call. We don't take everyone.

How it works

Three steps, in the order that compounds.

1Weeks 1–6
First principles
LLM APIs, context, memory, tool calling, RAG, embeddings, vector databases — in raw Python, so nothing stays magic.
2Weeks 7–9
Advanced architectures
Multi-agent orchestration, MCP, and the frameworks — learned after you know what they're hiding.
3Weeks 10–12
Production on AWS
Evals, CI/CD, Terraform, observability, guardrails, cost control. The part that separates a demo from a job.
Then · Weeks 13–26Capstone, industry fellowship, AWS certification, unlimited mock interviews, and coaching until you land the role.

Your first AI app is live in week 5 — a deployed chatbot trained on your own background that you can send to any interviewer.

Read the full curriculum
The person teaching you

I taught 3 million people data science. Then LLMs changed what mattered.

I started out as a consultant, taught myself engineering, and built one of the largest data and AI education communities in the world. Over 3 million students have come through our programs, and our graduates work at Amazon, Google, Meta, Accenture and NASA.

Then LLMs arrived and made most of what we were teaching secondary. So I rebuilt it from first principles — raw Python before frameworks, production deployment before theory, nothing that only works in a notebook. This is that program, and I teach the core of it myself.

Kirill EremenkoFounder, SuperDataScienceLinkedIn
Kirill Eremenko — Why I built this
Why I built this2 min

The reasons people don't make it — and what we do about them

"I'll start strong and drift."
A dedicated coach reviews your work every week, sets the plan, and holds the pace. Unlimited 1-on-1 calls and a private Slack channel with them.
"Every AI job asks for AI experience I don't have."
You do a real internship on real consulting projects and present your work to actual CEOs and COOs. The objection is gone before you apply.
"I can learn the material. I can't pass the interview."
Unlimited technical and behavioral mocks with people who have sat on the hiring side — then a post-mortem with your coach after every real interview.
"My CV doesn't say AI anywhere."
A full CV and LinkedIn rebuild around what you build here, reviewed in your first week by Tony — 12 years recruiting engineers at Google.
"I've done courses before and nothing changed."
90% hands-on, seven deployed systems, a public portfolio. Nothing here is watch-only.

Is this for you?

Yes, if
You've been shipping production code for five years or more
You can hold 4–6 hours a week for six months
You want a role, not a certificate
You want someone to tell you the truth about your work
Not yet, if
You've never written code professionally — start with the free masterclass
You want to train models rather than ship AI products. That's ML engineering, and it's a different path
You want a video library you work through alone
You're looking for a $99 course. This is a four-figure investment against a six-figure change in what you earn.

Graduates

"Thanks to their high-quality content and expert guidance, I was able to land a role as an AI Engineer working with LLMs."

LGLevi GarciaNow an AI Engineer

"I am 100% more confident in my ability to build with AI. This course will transform how you understand AI."

AOAlex OlthoffProgram graduate

"Having something real to show at the end, something I could actually deploy and share publicly, made the whole experience worth it."

PPrajaktaProgram graduate
3M+students taught
7systems deployed per graduate
17companies employing graduates

Who teaches

Not researchers, not YouTubers. Engineers who ship production AI and make it reliable.

Kirill Eremenko
SuperDataScience
Kirill Eremenko
Founder, SuperDataScienceFirst-principles AI · 3M+ students
Rohit Reddy
Meta
Rohit Reddy
MetaAI Engineering & AI Product Coach
Tony Chan
Google
Tony Chan
Ex-Google RecruiterCareer & Interview Coach
Gaurav Verma
AWS
Gaurav Verma
AWSAI System Design Coach
Mike Kofoed
Adobe
Mike Kofoed
AdobeAI Engineering Coach
Jorge Suarez
Indeed
Jorge Suarez
IBM, Deutsche Bank, IndeedAWS Prod Deployment Coach
Sara Selvaraju
AXS
Sara Selvaraju
Motorola, AXSAI Governance Coach
Neeraj Sujan
allNeurons
Neeraj Sujan
allNeurons, Agentic AI InstituteForward Deployed Engineer (FDE) Coach
Jean Weng
Transportation Logistics
Jean Weng
Transportation LogisticsPython Coach

Questions engineers actually ask

All 74 answers

No. You bring judgment, and everyone is equally new to this stack.

You've watched long enough.

This program isn't for everyone. We work with people who are serious about landing a high-paying AI role and want dedicated professional help — not another free course.

Because every student gets a dedicated coach, we only accept as many engineers as we have coaches for. If you qualify, we'll get on a strategy call and work out whether this is the right fit. If it is, we'll tell you. If it isn't, you'll leave with a clear picture of what to do instead.

See if you qualify

Not ready? The free masterclass runs live every week