Applied AI infrastructure fundamentals

The whole picture of an AI system, taught to the depth one real deployment needs.

Beginner technical·4 weeks·8 modules·24 lessons

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The 8 modules

Each one is a set of lessons and ends with one thing you keep. Open a module to see its lessons.

01See the whole AI systemFollow one request from the interface to the response, and name every part it passes through.3 lessons · ends with your architecture diagram and component glossaryOpen
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02APIs, hosted models and local open modelsMake the buy, run or host decision on evidence, and write down what it commits you to.3 lessons · ends with your model comparison and selection recordAccount
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03Compute, memory, storage and networkingSize the workload before you buy it, and find the bottleneck on paper first.3 lessons · ends with your capacity worksheet and cost estimateAccount
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04Data foundations and retrievalBuild a small retrieval workflow whose answers cite sources and whose failures are visible.3 lessons · ends with your retrieval test set, results and access rulesAccount
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05Package a reproducible serviceContainerize the application so a second person can run it without asking you anything.3 lessons · ends with your container build, configuration example and run instructionsAccount
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06Deploy and secure the endpointPut the service somewhere real, then prove that only the right requests get through.3 lessons · ends with your working endpoint and access test resultsAccount
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07Observe reliability, quality and costInstrument the service so you can tell an application failure from a model failure from a bill.3 lessons · ends with your operations dashboard and alert thresholdsAccount
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08Capstone: deploy a small AI serviceAssemble the whole system, break it once on purpose, and hand it over.3 lessons · ends with your completion recordAccount
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