The Applied AI blog
Field notes on building, shipping, and defending AI
Practical, curriculum-grounded writing on applied AI careers, MLOps, agentic AI, and what it actually takes to go from a notebook to a production system. 5 posts to start.
RAG in plain language: the skill behind every modern AI product
Retrieval-augmented generation is the difference between an AI that hallucinates and an AI that quotes your own documents. Here is what it is and why it matters.
What a defended capstone actually proves to an employer
A portfolio project you can explain under questioning is worth more than ten you cannot. Here is why the defense — not the build — is the point.
The data analyst path — without a computer science degree
You do not need a four-year CS degree to land a data analyst role. Here is the deliberate sequence that takes a recent high-school graduate to hireable.
Agentic AI vs. assistants: where the actual jobs are
An assistant answers; an agent acts. Understanding the difference is the fastest path to the roles hiring right now — AI Integration Manager, automation lead, and more.
From notebook to production: why MLOps is the real job
A model that works in a notebook is not a product. Here is what it actually takes to ship an AI system — and how the program trains for it.
Refer a friend — give two free classes
Know someone curious about applied AI? Send them your personal code. When they redeem it, they unlock the first two classes of any course free (a bonus on top of the standing one free class).
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