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NVIDIA NCP-AII Exam Overview:
| Certification Vendor: | NVIDIA |
|---|---|
| Exam Name: | NVIDIA Certified Professional – AI Infrastructure |
| Exam Number: | NCP-AII |
| Exam Duration: | 90 minutes |
| Exam Format: | Multiple Choice, Multiple Select |
| Real Exam Qty: | 50 |
| Available Languages: | English |
| Related Certifications: | NCP-DES NCP-AI |
| Certificate Validity Period: | 2 years |
| Passing Score: | 700 (scale of 0-1000) |
| Exam Price: | $195 USD |
| Sample Questions: |  |
| Exam Way: | Online proctored exam (Pearson VUE) |
| Pre Condition: | Recommended: hands-on experience with NVIDIA AI infrastructure products; basic knowledge of Linux, networking, and data center operations |
| Official Syllabus URL: | https://www.nvidia.com/en-us/certifications/ncp-ai-infra/ |
NVIDIA NCP-AII Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: NVIDIA AI Infrastructure Components | 25-30% | - NVIDIA networking solutions (Mellanox) - NVIDIA AI Enterprise software - Storage solutions for AI workloads - NVIDIA DGX systems |
| Topic 2: Deployment and Configuration | 25-30% | - Cluster configuration - Software deployment - Network configuration - System installation and setup |
| Topic 3: Monitoring and Management | 15-20% | - Performance monitoring - Troubleshooting basics - Resource utilization - NVIDIA management tools |
| Topic 4: AI Infrastructure Fundamentals | 15-20% | - GPU architecture basics - AI and Deep Learning concepts - Data center infrastructure requirements - NVIDIA software stack overview |
| Topic 5: Security and Best Practices | 10-15% | - Operational best practices - Compliance considerations - Security fundamentals |
Answers Every NCP-AII Candidate Should Read First
The NVIDIA AI Infrastructure exam is the official NVIDIA test registered under exam code NCP-AII. Passing it earns you the NVIDIA-Certified Professional certification, a credential at the Professional level. It is also linked to the related certifications: NCP-AI, NCP-DES. NVIDIA exams are valued because they test job-ready skills, so a passing score here carries real weight on a resume.
The NVIDIA AI Infrastructure exam includes 50 questions to be completed within 90 minutes. Do the pacing math before exam day: with that many items on the clock, you need a steady rhythm and the discipline to flag a hard question and move on instead of stalling. Two or three full timed sessions with the ActualCollection test engine will show you exactly what that pace feels like, so time pressure stops being a factor on the real day.
To pass the NVIDIA AI Infrastructure exam you need 700 (scale of 0-1000), and the official registration fee is $195 USD. A retake is not discounted: a failed attempt means paying the full $195 USD again, so treat your first sitting as the expensive one. A sensible rule is to book your seat only after you are scoring comfortably above the passing mark on the ActualCollection practice tests, not just squeaking past it once.
Recommended: hands-on experience with NVIDIA AI infrastructure products; basic knowledge of Linux, networking, and data center operations
Eligibility rules do change from time to time, so confirm the current requirements before you register on the official exam page.
Yes. ActualCollection offers a free PDF demo of the NVIDIA AI Infrastructure material so you can judge the question quality and format before spending anything. After purchase, your license includes 365 days of free updates, and if you want to keep receiving updates after that period, renewals are available at a 50% discount.
If you take the NVIDIA AI Infrastructure exam within 60 days of your purchase and do not pass, ActualCollection backs you with a 100% money-back guarantee. The claim must match the exam your product covers: attempts taken within 3 days of purchase are not eligible (that is too little preparation time), and neither are downloaded-but-unused products, free materials, or expired orders. The candidate name must match the payer name, and you need to submit a scanned enrollment slip plus the official Score Report PDF within 2 days of the exam; claims are processed within 7 days. Prefer not to refund? You can swap instead and receive two other exam products of equal value for free while keeping the update service on your original purchase.
Delivery itself is instant: your files are downloadable right away and emailed to you within one minute of payment. If nothing arrives within 2 hours, contact customer service. There is no limit on how many computers you may install the software on.
The official NVIDIA AI Infrastructure syllabus is organized into 5 domains. Key areas include NVIDIA AI Infrastructure Components (25-30%), AI Infrastructure Fundamentals (15-20%), and Deployment and Configuration (25-30%). The complete, up-to-date topic list appears in the exam topics section above; work through it line by line and flag anything you cannot yet explain in your own words.
NVIDIA AI Infrastructure Sample Questions:
Question 1
A researcher wants to allow a container to use only two specific GPUs out of four available ones (GPU 1 and GPU 2) on the host. The system is already set up for NVIDIA Docker with the container toolkit. Which Docker command will correctly assign only these GPUs to the container?
A. docker run --gpus '"device=0,1"' nvidia/cuda nvidia-smi --query-gpu=uuid --format=csv
B. docker run --rm --gpus 2 nvidia/cuda nvidia-smi
C. docker run --gpus '"device=0,3"' nvidia/cuda nvidia-smi --query-gpu=uuid --format=csv
D. docker run --rm --gpus '"device=1,2"' nvidia/cuda nvidia-smi
Question 2
During HPL execution on a DGX cluster, the benchmark fails with "not enough memory" errors despite sufficient physical RAM. Which HPL.dat parameter adjustment is most effective?
A. Set PMAP to 1 to enable process mapping.
B. Disable double-buffering via BCAST parameter.
C. Increase block size to 6144 to maximize GPU utilization.
D. Reduce the problem size while maintaining the same block size.
Question 3
During multi-node HPL burn-in, GPUs show uneven utilization. Which configuration ensures balanced workload distribution?
A. HPL_OOC_TILE_M to 8192 for larger blocks
B. Enable HPL_USE_NVSHMEM=1 for shared memory acceleration
C. Set --gpu-affinity and --cpu-affinity to align GPU and NUMA nodes
D. HPL_RUN_GEMM_TESTS to skip validation
Question 4
To validate bisectional bandwidth across two racks in a Spectrum-X Ethernet fabric, which NCCL test configuration isolates East-West traffic?
A. NCCL_TESTS_SPLIT= "OR 0x7" ./all_reduce_perf -g 8
B. NCCL_TESTS_SPLIT= "DIV 8" ./all_reduce_perf -g 1
C. NCCL_TESTS_SPLIT= "MOD 2" ./all_reduce_perf -g 8
D. Run without splits and analyze per-rack averages
Question 5
A machine learning platform stores multi-petabyte training datasets accessed concurrently by hundreds of GPUs. Administrators determine that the storage system must provide high aggregate throughput, parallel client access, and efficient scaling as additional storage nodes are added. Which storage solution is generally the most appropriate?
A. Individual SATA disks installed in each compute server
B. Parallel file system such as BeeGFS or Lustre
C. Local USB-attached storage
D. NFS server running on a single virtual machine
Solutions:
| Question 1 Answer: D | Question 2 Answer: D | Question 3 Answer: C | Question 4 Answer: C | Question 5 Answer: B |
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