NVIDIA Certified Professional: AI Infrastructure Exam Prep
The NVIDIA Certified Professional: AI Infrastructure (NCP-AII) exam validates system bring-up, hardware management, and control plane installation, gpu configuration, partitioning, and lifecycle management, cluster scheduling, containers, and ai workload runtime, network fabric, infiniband, and distributed communication performance. ExamPal publishes 281 premium questions and a 40-question free practice exam mapped across 5 blueprint domains. The local official-details index records: 60; 90 minutes; Multiple choice / multiple response. Candidates should verify current registration, pricing, and scoring details with the official exam authority before booking.
Exam Details
Exam Overview
Administered by
NVIDIA
Exam Format
60; 90 minutes; Multiple choice / multiple response
Passing Score
Verify current official exam guide
Exam Fee
Needs checkout recheck; vendor pricing can vary
Prerequisite
Review NVIDIA official certification page/outline saved locally.
Topics Covered
ExamPal covers all major topics tested on the NVIDIA Certified Professional: AI Infrastructure exam. Our questions are grounded in official study materials.
System Bring-up, Hardware Management, and Control Plane Installation
Covers initial server validation, out-of-band management, host software prerequisites, and installation/validation of NVIDIA AI infrastructure control plane components. It also includes platform connectivity, device topology, and physical rack-level checks needed to bring systems into a ready state.
GPU Configuration, Partitioning, and Lifecycle Management
Covers GPU operational state, persistence, MIG-enabled environments, Fabric Manager, and compatibility across firmware, driver, CUDA, and management tools. It also includes interpreting GPU error and event conditions to support lifecycle management and troubleshooting.
Cluster Scheduling, Containers, and AI Workload Runtime
Covers GPU scheduling with Slurm, GPU resource requests, containerized AI workloads, NVIDIA-optimized AI software stacks, and operational job control. It emphasizes validating resource allocation, runtime integration, and cluster utility output for workload execution and troubleshooting.
Network Fabric, InfiniBand, and Distributed Communication Performance
Covers validation of InfiniBand and high-speed network configuration, diagnostic tools, NCCL communication topology and behavior, communication performance measurement, distributed training troubleshooting, and cluster-level communication readiness. It emphasizes fabric health, topology selection, and performance verification for AI/HPC communication paths.
Monitoring, Diagnostics, Troubleshooting, and Performance Verification
Covers real-time GPU health monitoring, DCGM diagnostics, Xid and driver-related faults, thermal and power reliability issues, cluster test and performance verification, and interconnect or topology degradation. It focuses on using telemetry and benchmarks to isolate root cause and confirm production readiness.
Exam Blueprint
What the NVIDIA Certified Professional: AI Infrastructure Exam Tests
The exam is divided into 5 domains. Here is what each domain covers and how much weight it carries on the test.
Domain 1: System Bring-up, Hardware Management, and Control Plane Installation
24% of examCovers initial server validation, out-of-band management, host software prerequisites, and installation/validation of NVIDIA AI infrastructure control plane components. It also includes platform connectivity, device topology, and physical rack-level checks needed to bring systems into a ready state.
- 1.1 Validate server hardware readiness and perform initial bring-up
- Verify POST completion and BIOS/UEFI status
- Confirm detected CPU, memory, PCIe, GPUs, NICs
- Use platform tools and system logs
- Identify common bring-up failures
- 1.2 Manage out-of-band infrastructure using BMC/IPMI/Redfish
- Explain BMC role and capabilities
Key references: NCP-AII official exam guide · ExamPal shared topic tree
Domain 2: GPU Configuration, Partitioning, and Lifecycle Management
18% of examCovers GPU operational state, persistence, MIG-enabled environments, Fabric Manager, and compatibility across firmware, driver, CUDA, and management tools. It also includes interpreting GPU error and event conditions to support lifecycle management and troubleshooting.
- 2.1 Manage GPU operational state and persistence
- Inspect GPU inventory and utilization
- Enable or verify persistence mode
- Interpret GPU power and thermal state
- Validate driver communication with GPUs
- 2.2 Configure and manage MIG-enabled environments
- Explain MIG purpose and use cases
Key references: NCP-AII official exam guide · ExamPal shared topic tree
Domain 3: Cluster Scheduling, Containers, and AI Workload Runtime
18% of examCovers GPU scheduling with Slurm, GPU resource requests, containerized AI workloads, NVIDIA-optimized AI software stacks, and operational job control. It emphasizes validating resource allocation, runtime integration, and cluster utility output for workload execution and troubleshooting.
- 3.1 Configure and validate GPU scheduling with Slurm
- Explain Slurm GRES for GPUs
- Inspect node and partition configuration
- Verify GPU allocation behavior
- Drain resume or reconfigure nodes
- 3.2 Manage GPU resource requests for jobs
- Interpret GPU request syntax
Key references: NCP-AII official exam guide · ExamPal shared topic tree
Domain 4: Network Fabric, InfiniBand, and Distributed Communication Performance
22% of examCovers validation of InfiniBand and high-speed network configuration, diagnostic tools, NCCL communication topology and behavior, communication performance measurement, distributed training troubleshooting, and cluster-level communication readiness. It emphasizes fabric health, topology selection, and performance verification for AI/HPC communication paths.
- 4.1 Validate InfiniBand and high-speed network configuration
- Identify common network technologies
- Verify port and fabric status
- Confirm HCA discovery and functionality
- Detect common fabric issues
- 4.2 Use InfiniBand diagnostic and validation tools
- Validate fabric connectivity and path health
Key references: NCP-AII official exam guide · ExamPal shared topic tree
Domain 5: Monitoring, Diagnostics, Troubleshooting, and Performance Verification
18% of examCovers real-time GPU health monitoring, DCGM diagnostics, Xid and driver-related faults, thermal and power reliability issues, cluster test and performance verification, and interconnect or topology degradation. It focuses on using telemetry and benchmarks to isolate root cause and confirm production readiness.
- 5.1 Monitor GPU health and performance in real time
- Collect GPU health metrics
- Identify bottleneck-relevant metrics
- Monitor throttling reasons
- Establish alerting thresholds
- 5.2 Run and interpret DCGM diagnostics
- Execute appropriate DCGM diagnostics
Key references: NCP-AII official exam guide · ExamPal shared topic tree
Why study with ExamPal
Everything you need to prepare for and pass the NVIDIA Certified Professional: AI Infrastructure exam, in one app.
- 281 NCP-AII premium practice questions
- Free 40-question interactive practice exam
- 5 blueprint domains covered
- 43 glossary terms loaded from the shared terminology pack
- Detailed explanations and per-option rationales for study review
- Domain-level review paths with study guide, glossary, and static question pages
NVIDIA Certified Professional: AI Infrastructure Exam — Common Questions
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