NVIDIA-NCP-AII: NVIDIA-Certified Professional: AI Infrastructure

About the NVIDIA NCP-AII Exam

Master the NVIDIA-Certified Professional: AI Infrastructure (NCP-AII) exam — racking, commissioning, validating and troubleshooting the GPU clusters that AI workloads actually run on.

The complete practice exam for the NVIDIA-Certified Professional: AI Infrastructure (NCP-AII) exam. This is a professional-level credential aimed at the engineers who physically build AI clusters. Where the associate-level NCA-AIIO asks you to recognise what each component is for, NCP-AII asks you to install it, bring it up in the right order, prove it works, and work out which part failed when it does not.

The guide covers systems and server bring-up including the deployment and validation sequence, AI factory network topologies, BMC and out-of-band configuration, TPM, firmware upgrades on NVIDIA HGX systems, power and cooling validation, cable types and transceivers, and physical GPU installation; physical layer management including NVIDIA BlueField modes of operation and MIG partitioning for AI and HPC; control plane installation including NVIDIA Base Command Manager with high availability, cluster and OS installation, categories and interfaces, Slurm with Enroot and Pyxis, the GPU and DOCA driver lifecycle, the NVIDIA Container Toolkit, and the NGC CLI; cluster test and verification including single-node stress testing, High-Performance Linpack, NCCL bandwidth testing, NVLink Switch verification, cable signal quality, topology confirmation, ClusterKit node assessment and NeMo burn-in; and troubleshooting and optimisation including hardware fault isolation, GPU and power supply replacement, and server and storage performance tuning.

Who Should Take This Exam?

The NCP-AII certification is designed for data center engineers, AI infrastructure engineers, field and deployment engineers, and systems integrators who install and commission NVIDIA GPU estate in production. It validates professional-level depth: not just knowing that a cluster needs a burn-in, but knowing which test to run, in what order, what a passing result looks like, and what to do with the node when it fails.

You are expected to be comfortable with real hardware and the command line. The exam assumes you have physically worked on servers — racking, cabling, firmware, replacing parts — and can read the output of the tools that report on them.

Prerequisites: No hard prerequisite. NVIDIA recommends 2-3 years of operational experience in data center environments working with NVIDIA hardware, including GPU server installation, cluster bring-up and validation.

Typical study time: 6-10 weeks of focused study for an experienced data center or infrastructure engineer

Exam Quick Facts

Exam Domains & Weights

The NCP-AII exam is organised into 5 official domains, and NVIDIA publishes the domain weights in its Exam Study Guide. The percentages below are NVIDIA’s own published weights.

⚠️ How we allocated the practice questions: NVIDIA’s published weights are preserved exactly — they are the vendor’s numbers and we have not adjusted them. The practice-question counts, however, are not a strict pro-rata split. A literal 5% share would give Physical Layer Management only about 10 questions, which is too thin to practise against when it carries both BlueField modes of operation and the whole of MIG. That domain is therefore floored at 21 questions, and the difference is taken mostly from the two largest domains. Because this platform serves questions by per-question performance weighting, a domain’s share of the bank is effectively its share of your session — so the smallest domain is deliberately over-represented here relative to its 5% exam weight. Study to the official weights above; use the question counts as drill volume, not as a signal about exam emphasis.

💡 Study tip: The single biggest trap in this exam is treating a procedure as generic when it is platform-specific. A DGX A100 bring-up step is not an HGX B200 step, MIG behaves differently across GPU generations, and firmware paths diverge by chassis. Questions are written to catch anyone who has learned one platform’s runbook and assumed it generalises — so whenever you learn a procedure, note which platform it belongs to. Beyond that, learn the validation toolchain by what each tool uniquely proves rather than by name: nvidia-smi for device state and topology, NVSM for system health rollups, DCGM for continuous telemetry and diagnostics, HPL for sustained compute and thermals, NCCL for collective bandwidth across GPUs and nodes, ClusterKit for node-to-node assessment, and a NeMo burn-in for the full end-to-end path that the micro-benchmarks each miss. Finally, treat sequence as a first-class skill — a large share of professional-level questions are less “which command” and more “what is the correct next step, and what must already be true before it”.

Practice Exam — 194 Questions

Prepare for the NCP-AII with our 194-question practice exam covering all 5 official domains. Every question includes a detailed explanation and cites a first-party NVIDIA source.

What you get:

• ✅ Exam simulation mode with timer
• ✅ Spaced repetition for weak areas
• ✅ Detailed explanations for every question
• ✅ Progress tracking across domains
• ✅ 20 free questions — no account needed

Every citation in this bank points at NVIDIA’s own technical documentation — the product docs and the study guide’s own suggested reading — rather than blogs, marketing pages or third-party summaries. That keeps the bank smaller than one padded from looser sources, and it means the references stay valid as products move.

NVIDIA Certification Path

NCP-AII is one of two professional-level infrastructure certifications NVIDIA offers, alongside NCP-AIN (AI Networking). The associate-level NCA-AIIO is the usual starting point: it covers AI fundamentals, GPU infrastructure and cluster operations broadly, and it is worth holding the ideas from it in your head before attempting this exam.

The split between the two professional exams is a clean one. NCP-AII is about the cluster itself — the systems, the GPUs, the servers, and the deployment and validation of the compute estate. NCP-AIN is about the fabric that connects it: the switches, the transport, the congestion behaviour and the tools you reach for when a training job slows down and the GPUs are not the reason. If your day job involves racking, cabling, commissioning and validating GPU systems, this is the one that matches it.

Study Tips

1. Learn the bring-up sequence as a sequence — a large share of questions ask for the correct next action or the prerequisite that must already be satisfied; knowing the individual steps without their order will not get you through them
2. Use our practice exam — try the 20 free questions first to gauge your readiness
3. Always attach a procedure to its platform — DGX A100, DGX H100, HGX B200 and BlueField each have their own steps and their own firmware paths; answers that present one platform’s procedure as universal advice are a common distractor pattern
4. Know what each validation tool uniquely proves — HPL stresses sustained compute and cooling, NCCL measures collective bandwidth, ClusterKit assesses node-to-node behaviour, and a NeMo burn-in exercises the full training path including storage and the data pipeline that the micro-benchmarks never touch
5. Separate “enabled” from “usable” — MIG mode being on is not the same as having created instances, and several validation steps have this shape; learn the command that proves the second thing, not just the first
6. Practise reading tool output, not just running tools — the exam leans on interpreting what nvidia-smi, NVSM, DCGM and the diagnostic logs are telling you, including Xid and SXid signatures
7. Do not skip the small domain — Physical Layer Management is only 5%, but BlueField modes of operation and MIG are both genuinely intricate and are exactly where candidates lose easy marks
8. Check the official page — the official NCP-AII exam page always has the latest objectives and study guide