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Course 6: Deploying and Operating Agentic AI in Production
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What you will learn
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(a) Deploy an agent as a reliable, scalable service
(b) Cut cost and latency with caching, model routing, output limits, and batching
(c) Monitor agents in production with dashboards, alerts, and drift detection
(d) Manage the lifecycle: versioned prompts and models, rollbacks, and provider changes
Why take it
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(a) Takes an agent the last mile, from notebook to monitored service with a cost budget
(b) Every optimization is measured against its effect on quality
What makes it unique
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(a) Capstone of the specialization: the labs pick up the investment assistant built in earlier courses
(b) Ends with a production checklist and an operating model you can adapt to your organization