Course
AI & LLM Engineering
Learn how AI systems work inside, then build ones you can trust in production: the maths, machine learning, deep learning, transformers, RAG, harnesses, agents, evals, fine-tuning, MLOps and security. Every part ends with two projects you build yourself. Code in Python, NumPy and PyTorch, with Go where it fits.
from a dot product to a production assistant ↓
Route ticket
From
a dot product
To
a production AI system
- Stations
- 92
- Parts
- 11
- Reading time
- 182–280 h
- Languages
- Python · NumPy · PyTorch · Go
Your progress0 / 92
contents
The route
11 parts · 92 stations · 182–280 h
Terminal
Ride the whole line and you have built 22 projects, from a neural network in plain NumPy to a secure, evaluated, monitored AI assistant, and you can explain what happens inside every one.