LLM Application Architecture: From Prototype to Production
by Priya Raman
From first model to production inference, without the hand-waving.
Practical machine-learning and applied-AI courses for developers who want working systems rather than lecture notes. You learn the maths only where it changes a decision, then build classifiers, recommenders, retrieval pipelines and agents you can actually deploy. Every project runs on a laptop — no cluster required.
Showing 1–2 of 2 courses
Queues, caching, streaming, fallbacks and budgets: the architecture behind a reliable AI feature.
Design agents that plan, remember and stop, instead of looping until the budget is gone.
Other shelves developers move on to next.