Courses

30 project-based AI engineering courses across career and builder tracks. Every lesson is paired with a hands-on lab; the opening phases of 24 of 30 courses are free with no credit card.

Career track (22)

A sequenced path from fundamentals to production AI systems.

• ML & AI Engineering — From Python basics to production ML and AI systems
• Agentic AI Engineering — Design, build, evaluate, and deploy production-grade AI agents
• AI Security & Red Teaming — Secure, red-team, and defend production AI systems
• Forward Deployed AI Engineering — Embed inside enterprise clients, scope ambiguous problems, ship production AI on their infrastructure
• Voice & Conversational AI Engineering — Build, deploy, and optimize production-grade real-time voice AI agents
• Generative Media Engineering — Build, orchestrate, and deploy production-grade generative media pipelines
• AI Product Management — Ship AI features people actually trust — from opportunity to launch
• Testing AI-Written Code — Verify, test, and ship code from AI coding assistants with confidence
• Responsible AI Engineering — Build a deployable AI audit toolkit — bias detection, explainability, privacy, and governance in one pipeline
• Math for AI & ML — The math behind every ML algorithm — built in code, not on paper
• Core ML: Algorithms from Scratch — Build every classic ML algorithm by hand — then verify against scikit-learn
• Deep Learning from Scratch — Build your own mini PyTorch — autograd, layers, and training loops from the ground up
• Transformers & LLMs from Scratch — Pre-train a real 124M parameter GPT — tokenizer, data pipeline, training, and evaluation
• Computer Vision Engineering — From convolutions to ViTs — build models that see
• NLP & Speech Processing — From word embeddings to voice AI — build models that understand language
• Generative AI Fundamentals — From GANs to diffusion to flow matching — build and customize generative AI systems
• Reinforcement Learning — From bandits to RLHF — build agents that learn by doing
• Multimodal AI Systems — From CLIP to GPT-4V — build models that see, hear, and read
• Programming & CS Foundations — How to think like a programmer — from zero, before any AI or math content
• Engineering Practices & Tooling — The Missing Semester for AI Engineers — git, the command line, APIs, and the practical craft real jobs assume you already know
• Quantitative Foundations — Algebra, functions, and the math comfort you need before Math for AI & ML — not the math itself
• Data Analysis & Visualization — pandas, NumPy, and the daily skill of turning real (messy) data into an answer — not ML theory

Builder track (8)

Short, self-contained builds — ship one working thing in a weekend.

• Prompt Engineering Mastery — Get dramatically better results from any AI — for work, your side hustle, and everyday life
• Vibe Coding — Build real apps with AI — describe, review, debug, and ship without writing code from scratch
• Build Your First AI Agent from Scratch — A weekend build: a terminal agent that plans, calls tools, and remembers — no frameworks
• Build Your Own MCP Server — Give Claude access to your own data and tools — no framework required
• Build an Autonomous Coding Agent — Your own Claude Code — plan, edit, test, and commit, built from scratch
• Build a Multi-Agent Research Team — 5 specialist agents, 3 running in parallel, one cited report
• Master Claude Code for Production Shipping — CLAUDE.md, hooks, subagents, and CI — configured on your own real repo
• Security Review for Vibe Coders — The 5 real checks — and the exact prompts — that stop a vibe-coded app from becoming the next breach headline

Create a free account — the opening phases of 24 of 30 courses are free, no credit card. Or see Pro pricing.

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