Local AI and building systems
Learn the hardware, run a model, write small utilities, connect an API, and preserve structured facts.
Build and explain a small local prototype, including what it does not yet establish.
Understand the hardware a local model needs
Estimate memory before considering an upgrade.
Run a local model and verify the actual setup
Complete a small experiment before adding documents or agents.
Your first useful Python script: a document inventory
Read a practice folder and print a CSV without changing its files.
APIs and JSON: connect a model to a small program
Inspect a local request and distinguish syntax from accuracy.
Use a database to preserve facts and sources
Learn a small SQL example before designing a matter system.
Prompting, retrieval, or fine-tuning?
Choose the intervention that matches the failure.
Turn a prototype into a service you can maintain
Plan access, storage, monitoring, and recovery before adding users.
A useful way to work
Read in order for a gradual introduction, or use an individual lesson as a reference when a question comes up.
Code examples use Python 3 and its standard library unless stated otherwise. The local API example also requires a running model service. Commands with MODEL_TAG or YOUR_LOCAL_MODEL_TAG are placeholders to replace.