8 tracks, 119 full lessons. Every module is a lesson with real commands and code, a hands-on exercise, a printable cheat sheet, an architecture diagram and a five-question scenario quiz. Tick modules off as you go; pass a quiz and the module ticks itself.
Take code from a laptop to production safely and repeatedly: version control, containers, automated pipelines, Kubernetes, and infrastructure defined as code.
Keep production systems fast, available, and boring. Define reliability with numbers, see what your systems are doing, respond well when they break, and engineer them to break less.
Build with AI, not just talk about it: enough machine-learning grounding to reason clearly, then LLM applications, agents and tools, and finally running models in production — including using AI to run production itself.
Think like an attacker, build like a defender. Threat models, identity, cryptography and hardening first; then securing containers, cloud and the pipeline; then detection, response and the compliance questions engineers actually get asked.
Move data reliably and model it so people can trust it: SQL and modelling first, then batch pipelines and orchestration, then warehouses, Spark and streaming, and finally observability and governance for a platform others depend on.
Robotics is where code meets the physical world, and it is one of the most in-demand skills of the decade. This track takes you from the electronics and the first microcontroller through sensors, motors, control, ROS 2, computer vision and navigation — and, because robotics needs hardware, it tells you exactly what to buy, where, and how to do it cheaply.
Blockchain and Web3 are among the most hyped — and most misunderstood — areas in tech. This track cuts through the noise: what a blockchain really is, the cryptography beneath it, how Ethereum and smart contracts work, and how to write, test and deploy your own contracts and dApps in Solidity. It stays honest about what the technology is genuinely good for and what it isn't.
Structured preparation for the exams employers ask about: what each domain really covers, a realistic study plan, hands-on labs where the exam is practical, cheat sheets, and practice questions written in the exam's own style.
They overlap on purpose — most engineers end up needing several. Start with the one closest to your job today.
Start here if you're a developer who wants to own deployments, or you're new to infrastructure. It is the foundation the other tracks build on.
Start here if you already deploy software and now carry a pager, or you're moving from operations or sysadmin work toward an engineering role.
Start here if you want to build LLM-powered products or bring AI into operations. Platform engineers: skim Stage 1 and begin at Stage 2.
Start here if you're asked to 'make it secure' and want more than a checklist, or you're moving toward AppSec, cloud security or DevSecOps.
Start here if you write SQL and Python and want to own pipelines and platforms, or you're an analyst moving toward engineering.
Start here if you want to build real, moving machines — for a career in robotics, automation or embedded systems, for a competition, or just because it is the most fun engineering there is. No hardware yet? The kit lesson gets you a capable starter setup for the price of a few coffees a month.
Start here if you want to understand blockchain properly — to build on it, to work in the space, or just to separate the real engineering from the hype. You'll write and deploy actual smart contracts on free test networks, so it costs nothing to learn.
Start here if you have an exam date, or want a structured way to prove skills you already use. Pair each guide with its track.
New modules and projects are added regularly. If a lesson is wrong, unclear or missing something you needed, say so — it gets fixed.
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