Go from
Software Engineer
to AI Engineer
Join 2,000+ developers who learned to ship AI models in production. Live instruction. Real projects. Zero cost.
Join students from Google, Stripe, Netflix & more
★★★★★ Rated 4.9/5 by 2,000+ developers
Most AI courses are
too slow, too expensive, or too theoretical
You don't need another 40-hour video course you'll never finish. You don't need a $10,000 bootcamp that puts you in debt. You need live instruction, real accountability, and projects that make hiring managers stop scrolling.
Self-paced courses
87% of people who buy online courses never finish them. Without accountability, motivation dies.
$10K+ bootcamps
Expensive programs teach the same theory with toy datasets. You graduate with debt, not a portfolio.
University programs
2 years of math proofs before you write real code. By the time you graduate, the tools have changed.
12-Week Battle-Tested Curriculum
From Python basics to production MLOps. Every week ships a new project.
Month 1
Foundations & Classical ML
— Course intro, AI landscape, Python env setup
— NumPy & Pandas crash course for developers
— Linear algebra for ML: vectors, matrices, dot products
— Probability & statistics essentials
— ML fundamentals: supervised vs unsupervised, train/test split
— Build first model: linear regression from scratch (NumPy)
— Scikit-learn: logistic regression, decision trees, random forests
— End-to-end: spam classifier with proper evaluation
Month 2
Deep Learning & Modern AI
— Neural networks: perceptron, backpropagation intuition
— Build a neural net from scratch (NumPy)
— PyTorch basics: tensors, autograd, training loops
— CNNs for computer vision: architecture + transfer learning
— NLP & Transformers: how attention works (intuition-first)
— Fine-tune BERT for sentiment analysis (Hugging Face)
— LLMs: prompting, RAG basics, embeddings
— Build a RAG chatbot with LangChain + OpenAI/Local LLM
Month 3
Production & Job Readiness
— From notebook to production: FastAPI model serving
— Dockerize your ML app, API design for ML
— MLOps basics: experiment tracking (MLflow), model versioning
— CI/CD for ML: GitHub Actions, testing ML pipelines
— Cloud deployment: AWS SageMaker / GCP Vertex / Render
— Monitoring, logging, and model drift detection
— Portfolio review, GitHub polish, technical interview prep
— Capstone presentations, community showcase, next steps
6 Projects That Get You Hired
Not toy examples. Real applications you can put on your resume today.
Spam Classifier API
End-to-end ML pipeline with scikit-learn, exported to a FastAPI microservice with Docker.
Neural Net From Scratch
Build and train a feedforward network using only NumPy. Understand backprop at the matrix level.
Image Classifier with CNNs
Fine-tune a ResNet on a custom dataset using PyTorch. Deploy with Gradio.
Sentiment Analysis Engine
Fine-tune BERT for Twitter sentiment. Package as a reusable Python library.
RAG Chatbot
Build a document-QA bot with LangChain, vector DB, and local LLMs. Production ready.
MLOps Pipeline
Full CI/CD for ML: experiment tracking, model registry, automated retraining with GitHub Actions.
Students Who Transformed Their Careers
Real developers. Real results. All from this free course.
“I spent $3,000 on a bootcamp that taught me less in 6 months than this free course did in 12 weeks. The live coding sessions are gold. I got 3 interview offers after Week 8.”
“The top-down approach clicked for me. Instead of drowning in math proofs, I was shipping working models by Week 3. My GitHub went from 50 to 2,000 stars in one cohort.”
“I was skeptical because it was free. But the community accountability kept me showing up. The MLOps module alone helped me productionize a model at work that saves us $200K/year.”
“Best free resource on the internet, period. The RAG chatbot I built in Week 8 became the core of our startup's product. I owe my entire career pivot to this course.”
“The Discord community is incredibly supportive. Having 500+ developers debugging together at 2 AM made the hard weeks manageable. Finished with 6 portfolio projects.”
“I went from zero Python to deploying LLM APIs in production. The instructor explains complex concepts like you're a smart friend, not a PhD student.”
12 Years Experience
Ex-Google, Ex-OpenAI
Learn from Someone Who's Built & Shipped AI at Scale
I spent 8 years as a Staff ML Engineer at Google and 3 years leading AI infrastructure at OpenAI. I've interviewed 200+ ML engineers. I know exactly what hiring managers look for — and what's missing from most courses.
This course is everything I wish existed when I made the switch from backend engineering to ML. No fluff. No gatekeeping. Just the exact skills that got me hired, promoted, and trusted with billion-parameter models.
We Ship Models.
They Ship Theory.
Most AI courses are either too slow, too expensive, or too theoretical. We built this for developers who want to ship AI in production, not write proofs on a whiteboard. Live instruction. Real tools. A community that keeps you accountable. And it's completely free.
Start Learning Free$49/mo
$11,000
Free (self-paced)
$$$$
How We Teach
Top-Down
Show working code first, then explain theory. See it work, then understand why.
Code-Along
Live coding in every session. Students follow along in real time.
GitHub-Centric
All code, assignments, and solutions in public repos. Build in the open.
Real Tools
Production libraries only: PyTorch, Hugging Face, FastAPI. No toy examples.
Homework
30-60 min between sessions: reading or a small coding challenge.
Free Tool Stack
Everything you need is free. No expensive subscriptions required.
Zero Cost. Maximum Value.
We believe talent is everywhere. Opportunity isn't. Here's what you get:
Full Course Access
Everything you need to become an AI engineer. No credit card. No catch.
- ✓ 24 live sessions (2/week)
- ✓ 6 portfolio projects
- ✓ Private Discord community
- ✓ Session recordings
- ✓ Verified certificate
- ✓ GitHub code reviews
- ✓ Job referral network
1,953 developers enrolled this month
Pro Mentorship
For developers who want 1:1 guidance and career acceleration.
- ✓ Everything in Free
- ✓ Weekly 1:1 calls with instructor
- ✓ Resume & LinkedIn review
- ✓ Mock technical interviews
- ✓ Direct intro to hiring partners
- ✓ Lifetime community access
- ✓ Priority support
Only 20 spots per cohort
Frequently Asked Questions
Yes. No credit card required. No hidden fees. We believe quality AI education should be accessible to every developer. We make money through corporate training and optional 1:1 mentorship.
You should have 2+ years of professional software development experience and be comfortable with Git. No prior ML or Python experience required — we teach Python from a developer's perspective.
All sessions are recorded and uploaded within 2 hours. You also get access to our private Discord where TAs answer questions 24/7. Most students rewatch recordings at 1.5x speed.
Yes. Upon completing all 6 portfolio projects and attending 80% of sessions, you receive a verified certificate you can share on LinkedIn. Our certificates are recognized by 200+ hiring partners.
Most free courses are pre-recorded videos with zero accountability. Ours is live, cohort-based, with a community of 500+ developers going through it together. You don't just watch — you build, ship, and get hired.
Your AI Career Starts in 12 Weeks
Cohort 2 launches soon. Only 47 spots left.
12 weeks. 2 hours/week. Completely free.