The whole catalog, ecosystem by ecosystem
Complete, self-paced guides ordered into ecosystems that run from fundamentals to production. Each ecosystem is built from what real job postings actually ask for.
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AI Engineering 5: Product and Client
Fifth track of the AI Engineering ecosystem: what an AI engineer needs from product work and client work, at the level of the engineer who builds. Decide whether a feature needs AI and how much autonomy it gets, measure it with users against the baseline, instrument the events that answer those questions, and run a client engagement end to end: discovery, scope, success as evals, a costed proposal, a pilot, and handoff. Each guide stands alone, with its own case and code that runs without an API key. Assumes intermediate Python and having called an LLM from code.
In order, from fundamentals to production. Start at 1.
3 courses
AI Product Decisions for Engineers Guide
Ya sabes llamar a un LLM desde código.
IntermediateProduct Analytics Instrumentation
Knowing which metric to watch is useless if the data behind it is recorded badly.
Intermediate64 lessonsClient-Facing AI Engineering Guide
More than half of AI engineer job postings ask for something that is not code.
Intermediate