Generative AI & Large Language Models
How large language models really work — and how to build reliable products on top of them.
16 courses across the modern technology stack. Every course opens with 5 complete, free lectures — no account needed.
How large language models really work — and how to build reliable products on top of them.
Real intuition for how machines learn from data — models, loss, gradients and generalization.
Neural networks from the ground up — neurons, backpropagation, optimizers and the techniques that make deep models train.
How agents learn by trial and error — bandits, Markov decision processes, value functions and Q-learning.
How machines see — pixels, convolutions, CNNs and the models behind recognition and object detection.
Turn text into insight — tokenization, classification, word embeddings, entity extraction and semantic search.
Take models from notebook to production — pipelines, experiment tracking, serving, monitoring and drift.
The linear algebra, calculus and probability behind machine learning — every idea made visual.
Follow data across the internet — addresses, layers, routing and reliable delivery.
Write clear, correct Python — with a precise mental model of what your code does.
See how browsers turn code into pages — HTML, CSS, JavaScript and the event loop.
Processes, scheduling, concurrency and memory — the machinery under every program.
Package, ship and run software reliably — from Dockerfiles to self-healing clusters.
Think like an attacker, defend in layers, and understand the cryptography that protects everything.
Model, query and protect relational data — and understand what happens inside the database.
Design systems that scale — load balancing, caching, replication and asynchronous processing.
Combine these courses into learning paths for each role — developers, operators, data and security teams — with team pricing and a walkthrough before you commit.
Combine courses into role-based learning paths for your engineers, with team pricing.