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Building AI Apps with LLMs
From first API call to a feature you can ship: prompting, structured output, tool calling, streaming, and cost control.
Intermediate2h 27m4 modules26.4k students
What you'll learn
sparkles
Understand the model
Reason about tokens, context windows, and sampling instead of treating the model as a black box.
code
Get structured output
Make a model return data your program can rely on, and validate it before you use it.
workflow
Wire up tool calling
Let the model call your functions, and keep the loop bounded and observable.
gauge
Ship it affordably
Stream responses, cache what repeats, and keep latency and spend under control.