121 practice questions for NVIDIA Agentic AI Professional (NCP-AAI), with full explanations.
Every question comes with the correct answer, the reasoning behind it, and a short note on why each wrong option is wrong. Work through it once with the answers, then again with the questions-only copy under exam conditions.
- 121 questions mapped to the NCP-AAI exam blueprint, across all ten domains
- Answers and explanations for every question, including why each wrong option is wrong
- A questions-only PDF for timed practice runs
- Instant delivery by email the moment you check out
- Free monthly updates for as long as the exam is live
- Pass or your money back
An NCP-AAI attempt costs US$200. This pack is US$39, paid once.
Try 10 questions free before you buy.
Last updated September 2026 · 121 questions
What makes the NCP-AAI hard
NCP-AAI is the newest professional exam in NVIDIA’s catalogue, introduced in late 2025 to cover agentic AI end to end. It runs to 60 to 70 questions in 120 minutes, remote-proctored through Certiverse, and unlike the infrastructure exams it is a developer’s exam about designing, building, evaluating and running LLM agents rather than racking GPUs. NVIDIA publishes ten weighted domains, and the two largest are the two you would expect.
Agent Architecture and Design and Agent Development are 15% each. Architecture covers reactive, reasoning-based and hybrid agent designs, frameworks such as ReAct, single-agent versus multi-agent patterns, and communication, orchestration and tool integration between agents. Development covers building agents with LangChain, LangGraph, AutoGen, CrewAI and the NeMo Agent Toolkit, tool calling, error handling, prompt engineering and multimodal inputs. Evaluation and Tuning and Deployment and Scaling are 13% each: metrics and benchmarks, A/B testing and deciding when to fine-tune versus prompt, then containers, Kubernetes, scaling strategies and cost.
The remaining domains sit at 5 to 10%: Cognition, Planning and Memory covers chain-of-thought, task decomposition and short versus long-term memory; Knowledge Integration and Data Handling covers RAG pipelines, chunking, vector databases and data quality; NVIDIA Platform Implementation covers NIM microservices, Triton Inference Server, TensorRT-LLM and NeMo Guardrails; and Run, Monitor and Maintain, Safety, Ethics and Compliance, and Human-AI Interaction and Oversight round out the blueprint. Candidates report the cognition and ethics questions as the hardest, because they apply a framework to a production scenario rather than ask you to define it.
About the exam
NCP-AAI (NVIDIA-Certified Professional: Agentic AI) is an intermediate-level certification validating the ability to architect, develop, deploy and govern agentic AI solutions with multi-agent interaction, distributed reasoning, scalability and ethical safeguards. NVIDIA recommends one to two years of AI and ML experience with production agentic projects.
Exam domains
- Agent Architecture and Design: 15%
- Agent Development: 15%
- Evaluation and Tuning: 13%
- Deployment and Scaling: 13%
- Cognition, Planning, and Memory: 10%
- Knowledge Integration and Data Handling: 10%
- NVIDIA Platform Implementation: 7%
- Run, Monitor, and Maintain: 5%
- Safety, Ethics, and Compliance: 5%
- Human-AI Interaction and Oversight: 5%
60 to 70 questions, 120 minutes, US$200 per attempt, online remote proctored through Certiverse. NVIDIA does not publish a passing score for this exam. Certification valid for two years.
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