66 practice questions for NVIDIA AI Operations Professional (NCP-AIO), 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.
- 66 questions mapped to the NCP-AIO exam blueprint, across all four 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-AIO attempt costs US$500. This pack is US$39, paid once.
Try 10 questions free before you buy.
Last updated September 2026 · 66 questions
What makes the NCP-AIO hard
NCP-AIO is the day-two exam. Where NCP-AII asks whether you can build the cluster, AI Operations asks whether you can run it: provision it, schedule work on it, share the GPUs fairly, and fix it when Slurm, Kubernetes or a Fabric Manager service misbehaves. NVIDIA rebuilt the format in 2026: it is now 30 multiple-choice questions plus three hands-on lab exercises, all inside one 120-minute session, with the lab environment provisioned automatically when the exam starts. That makes it the only NVIDIA professional exam where you are marked on what you configure, not just what you know, and it is built around NVIDIA’s own management stack, so generic Kubernetes administration experience only gets you part of the way.
Installation and Deployment is the largest domain at 31%: installing and configuring Base Command Manager, initialising Kubernetes on NVIDIA hosts, deploying containers from NGC and cloud VMI images, storage requirements for AI data centres, and deploying DOCA services on BlueField DPU Arm cores. Administration, Workload Management, and Troubleshooting and Optimization are 23% each. Administration covers Fleet Command, Slurm cluster management, AI data centre architecture, BCM cluster provisioning, Run:ai administration and configuring Multi-Instance GPU for AI and HPC workloads.
Workload Management covers administering Kubernetes clusters, keeping workloads efficient through scheduling and quotas, and the system management tools used to resolve operational issues. Troubleshooting and Optimization covers Docker, the Fabric Manager service for NVLink and NVSwitch systems, Base Command Manager and the Magnum IO components, and GPU performance tuning. The multiple-choice half describes a job stuck in the queue or a node dropping out of the fabric and asks for the first diagnostic step; the lab half expects the commands to actually be run, so practise on a real cluster rather than just reading about one.
About the exam
NCP-AIO (NVIDIA-Certified Professional: AI Operations) is an intermediate-level certification validating the ability to administer, deploy, manage and troubleshoot NVIDIA AI infrastructure in data centre and edge environments: administration with BCM, Slurm, Run:ai and MIG, workload management on Kubernetes, installation and deployment, and troubleshooting and optimisation. NVIDIA recommends hands-on experience operating NVIDIA AI infrastructure.
Exam domains
- Administration: 23%
- Workload Management: 23%
- Installation and Deployment: 31%
- Troubleshooting and Optimization: 23%
30 multiple-choice questions plus 3 hands-on lab exercises, 120 minutes total, US$500 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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