Course

Open Source & Local AI

You don't have to rent AI from a company — some of the best models are open: you download the whole thing and run it yourself, with no bill, no internet, and nothing leaving your device. This course is the plain-language tour: what 'open weights' means and why you'd run a model yourself, the main open families (Llama, DeepSeek, Mistral, Qwen, Gemma) and what each is good at, the free apps that make it a one-click download, how shrinking a model (quantization) fits it on a normal laptop, the privacy and offline wins, the real cost math versus a paid API, and a simple checklist for whether to go local. One live scene per idea, no version numbers to go stale.

7 lessonsBeginner41 min

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Course lessons

Run AI yourself

You don't have to rent AI from a company — some of the best models are yours to download and run, free and offline. That's what 'open weights' unlocks.

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The open-weights families

Llama, DeepSeek, Mistral, Qwen, Gemma — a handful of open families cover most needs. A quick map of who's good at what.

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Tools to run them

Apps like Ollama and LM Studio turn 'run a model yourself' into a one-click download and a chat window. No command line required.

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Distilled & quantized

A giant model won't fit a normal laptop — until you shrink it. Quantization trims its size so it runs on your machine, for a little less sharpness.

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Privacy & offline

When a model runs on your machine, your words never leave it — no server, no internet, nothing logged elsewhere. That's the quiet superpower of local AI.

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Cost: hardware vs API

Local AI is 'free' per use but you buy the hardware; an API is pay-as-you-go. Which is cheaper flips with how much you use it.

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Should you go local?

Local AI shines for privacy, offline, and heavy steady use — but asks for hardware and setup. A quick checklist for whether it's right for you.

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