NCP-AAI Practice Tests

NVIDIA Agentic AI Professional

Prepare for NVIDIA-Certified Professional Agentic AI with practice for agent architecture, development, evaluation, deployment, cognition, RAG, NVIDIA platform implementation, operations, safety, and human oversight.

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Duration

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Questions

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Cost

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Where to register

NVIDIA

Issued by NVIDIA. Delivered via Certiverse. NVIDIA lists the agentic AI professional exam registration and blueprint from the certification page.

01·Overview

Certification overview

The format, prerequisites, and what to expect on exam day.

Exam details

Exam Code
NCP-AAI
Duration
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Questions
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Format
Certification exam
Passing Score
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Cost
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Validity
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Prerequisites

Professional-level understanding of agentic AI architecture and production deployment
Experience with tool use, function calling, agent orchestration, RAG, evaluation, monitoring, and governance
Familiarity with NVIDIA NIM, NeMo Agent Toolkit concepts, Triton, Kubernetes, MCP, A2A, and safety controls

02·Domains

Exam domains

Topics on the official blueprint, with their relative weight.

Agent Architecture and Design

15%

ReAct, ReWOO, and reasoning patterns
Routing and prompt chaining
Multi-agent collaboration
Workflow versus autonomous-agent tradeoffs

Agent Development

15%

Tool and function definitions
Structured output and function calling
Workflow configuration
LangChain, LangGraph, CrewAI, LlamaIndex, and AutoGen integration

Evaluation, Tuning, Deployment, and Scaling

26%

Agent evaluation harnesses
LLM-as-a-judge and trajectory evaluation
Profiling and sizing
NIM, Triton, Kubernetes, MCP, and A2A runtimes

Cognition, Planning, Memory, and Knowledge Integration

20%

Interleaved reasoning and acting
Planning and execution
Short-term and long-term memory
RAG pipelines, embedders, retrievers, reranking, and multimodal retrieval

Platform, Operations, Safety, and Oversight

22%

NIM API Catalog and build.nvidia.com
Telemetry, profiling, and health checks
NemoGuard and jailbreak detection
Human-in-the-loop checkpoints, authentication, and auditability

03·Key topics

What you actually study

Service families and concept clusters that show up across questions.

Agent Patterns

ReAct
ReWOO
orchestrator-workers
routing
tool-calling

Frameworks and Protocols

LangGraph
CrewAI
LlamaIndex
AutoGen
MCP
A2A

NVIDIA Platform

NIM
Triton
NeMo Agent Toolkit concepts
NIM Blueprints
build.nvidia.com

Governance

Telemetry
NemoGuard
prompt injection defense
human oversight
authentication

04·Study tips

How to actually pass it

Practical strategies for the weeks before, and the morning of.

Preparation strategy

Practice choosing agent patterns based on determinism, autonomy, latency, and tool complexity.
Review RAG, reranking, memory, reflection, function calling, and structured output as agent building blocks.
Study deployment and runtime choices across NIM, Triton, Kubernetes, MCP, and A2A.
Treat safety, authentication, telemetry, and human oversight as core production requirements.

Exam day

Identify the product family first, then match the answer to the service or platform named in the scenario.
Watch for requirements around cost, latency, governance, and operational ownership.
Use elimination on answers that ignore security, monitoring, or responsible AI requirements.
Flag long architecture questions and return after completing faster recall questions.
Choose managed services when the question emphasizes speed, governance, and reduced operations.

Prepare for production agentic AI architecture.

Practice agent patterns, development, evaluation, deployment, RAG, safety, and oversight. Start free, no card required.

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