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Join this new short course on Nvidia’s NeMo Agent Toolkit, taught by Brian McBrayer, Solutions Architect in Generative AI at Nvidia.
Many teams struggle to turn agent demos into reliable systems that are ready for production. Nvidia’s open-source NeMo Agent Toolkit (NAT) provides the building blocks you need to harden your agents for production, whether built in raw Python, LangGraph, CrewAI, or any other framework.
NAT makes it easy to add observability, run systematic evaluations, and deploy with production features like authentication and rate limiting. In this course, you’ll build a climate data analysis agent using configuration-driven workflows, add OpenTelemetry tracing to debug agent reasoning, measure performance improvements, and deploy with a professional interface. You’ll also expand to multi-agent workflows where specialized agents built with different frameworks collaborate on complex tasks.