NVIDIA NCP-AAI: Agentic AI Certification Prep

About this course

This course contains the use of artificial intelligence.

This course is exam-focused preparation for the NVIDIA-Certified Professional: Agentic AI (NCP-AAI) credential, built by Aseem Mankotia around the six published exam objective areas. Agentic and multi-agent AI is the fastest-moving area of the AI market right now, and NCP-AAI is one of the first professional-tier credentials built specifically around it — this course walks through agent architectures and reasoning paradigms (ReAct, plan-and-execute, tree-of-thought), multi-agent orchestration patterns across LangGraph, CrewAI, AutoGen and the NVIDIA NeMo Agent toolkit, memory and retrieval design, tool integration including the Model Context Protocol, and deployment on the NVIDIA stack (NIM, Triton, TensorRT-LLM, NeMo Guardrails and Retriever). Every chapter is scenario-first: the real exam skill NVIDIA tests is choosing the BEST architecture, pattern, or control for a described production situation, not reciting definitions.

Aseem Mankotia structures each chapter around the classic decision pairs the exam leans on — single-agent vs multi-agent, ReAct vs plan-and-execute, supervisor/worker vs hierarchical vs collaborative orchestration, short-term vs long-term memory, RAG vs long-context, and human-in-the-loop vs fully autonomous control — paired with hands-on framework walkthroughs (build a ReAct agent, wire a LangGraph supervisor graph, add an MCP tool, layer in NeMo Guardrails) so the concepts are tied to something you actually build and inspect. Labs are designed at a read-and-understand depth appropriate for exam prep: you follow exact commands, see expected output, and connect each step back to a specific exam objective.

Note on domain weighting: NVIDIA has not published official per-domain percentages or a passing score for NCP-AAI, so the weights shown throughout this course (marked with a leading ~) are editorial estimates reflecting the emphasis in NVIDIA's published exam guide, not official NVIDIA figures. T

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