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Exam Overview
Exam Code NCP-AIO
Exam Name NVIDIA Certified Professional AI Operations
Vendor NVIDIA
Total Questions 66
Last Updated 26-Oct, 2026
Free NCP-AIO Questions Get Premium Access
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Free NCP-AIO Practice Questions

Explore 8 free practice questions for the NVIDIA NCP-AIO exam and review the answers and explanations to support your preparation.

  1. Question 1

    Single answer
    A Slurm user needs to submit a batch job script for execution tomorrow. Which command should be used to complete this task?
    • Option A:
      sbatch -begin=tomorrow
      Correct
    • Option B:
      submit -begin=tomorrow
      Correct
    • Option C:
      salloc -begin=tomorrow
      Correct
    • Option D:
      srun -begin=tomorrow
      Correct
    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer: A

    Explanation

    Comprehensive and Detailed Explanation From Exact Extract: In Slurm cluster administration, the command to submit a batch job script is sbatch. This command schedules the job to be executed by the Slurm workload manager. The option -begin=tomorrow (or -- begin=tomorrow) specifies the start time for the job execution, which in this case is set for tomorrow. The other commands have different purposes: submit is not a valid Slurm command. salloc is used to allocate resources interactively but does not submit batch jobs for scheduled execution. srun runs jobs immediately on allocated resources but is typically used to launch tasks in an active job or interactively, not for batch job submission. Therefore, the correct command to submit a batch job script for future execution is sbatch - begin=tomorrow.

  2. Question 2

    Single answer

    A system administrator needs to optimize the delivery of their AI applications to the edge. What NVIDIA platform should be used? 

    • Option A:
      Base Command Platform
      Correct
    • Option B:
      Base Command Manager
      Correct
    • Option C:
      Fleet Command
      Correct
    • Option D:
      NetQ
      Correct
    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer: C

    Explanation

    NVIDIA Fleet Command is the platform designed specifically to optimize and manage the deployment and delivery of AI applications at the edge. It enables secure and scalable orchestration of AI workloads across distributed edge devices, providing lifecycle management, remote monitoring, and updates. Fleet Command facilitates running AI applications closer to where data is generated (edge), improving latency and operational efficiency. Base Command Platform and Base Command Manager primarily target data center and AI cluster management for configuration, monitoring, and troubleshooting. NetQ is focused on network telemetry and network state monitoring rather than application delivery. Therefore, for AI application delivery and optimization at the edge, Fleet Command is the recommended NVIDIA platform.

  3. Question 3

    Single answer

    You are a Solutions Architect designing a data center infrastructure for a cloud-based AI application that requires high-performance networking, storage, and security. You need to choose a software framework to program the NVIDIA BlueField DPUs that will be used in the infrastructure. The framework must support the development of custom applications and services, as well as enable tailored solutions for specific workloads. Additionally, the framework should allow for the integration of storage services such as NVMe over Fabrics (NVMe-oF) and elastic block storage. Which framework should you choose?

    • Option A:
      NVIDIA TensorRT
      Correct
    • Option B:
      NVIDIA CUDA
      Correct
    • Option C:
      NVIDIA NSight
      Correct
    • Option D:
      NVIDIA DOCA 
      Correct
    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer: D

    Explanation

    Comprehensive and Detailed Explanation From Exact Extract: NVIDIA DOCA (Data Center Infrastructure-on-a-Chip Architecture) is the software framework designed to program NVIDIA BlueField DPUs (Data Processing Units). DOCA provides libraries, APIs, and tools to develop custom applications, enabling users to of load, accelerate, and secure data center infrastructure functions on BlueField DPUs. DOCA supports integration with key data center services including storage protocols such as NVMe over Fabrics(NVMe-oF), elastic block storage, and network security and telemetry. It enables tailored solutions optimized for specific workloads and high-performance infrastructure demands. TensorRT is focused on AI inference optimization. CUDA is NVIDIA’s GPU programming model for general-purpose GPU computing, not for DPUs. NSight is a development environment for debugging and profiling NVIDIA GPUs. Therefore, NVIDIA DOCA is the correct framework for programming BlueField DPUsin a data center environment requiring custom application development and advanced storage/networking

  4. Question 4

    Single answer

    A system administrator needs to collect the information below:
    GPU behavior monitoring
    GPU configuration management
    GPU policy oversight
    GPU health and diagnostics
    GPU accounting and process statistics
    NVSwitch configuration and monitoring
    What single tool should be used?

    • Option A:
      nvidia-smi
      Correct
    • Option B:
      CUDA Toolkit
      Correct
    • Option C:
      DCGM
      Correct
    • Option D:
      Nsight Systems
      Correct
    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer: C

    Explanation

    Comprehensive and Detailed Explanation From Exact Extract:
    The NVIDIA Data Center GPU Manager (DCGM) is the comprehensive management tool that provides all the requested functionalities: monitoring GPU behavior, managing configurations, enforcing policies, health diagnostics, process accounting, and NVSwitch monitoring. DCGM is designed for large-scale GPU management in data centers and AI clusters, providing detailed telemetry and control over NVIDIA GPUs and NVSwitches.
    nvidia-smi provides GPU monitoring but lacks full policy and NVSwitch management.
    CUDA Toolkit is for GPU programming and development.
    Nsight Systems is focused on performance profiling and debugging.
    Therefore, DCGM is the single tool that meets all the listed requirements.

  5. Question 5

    Single answer

    A system administrator notices that jobs are failing intermittently on Base Command Manager due to incorrect GPU configurations in Slurm. The administrator needs to ensure that jobs utilize GPUs correctly.
    How should they troubleshoot this issue?

    • Option A:
      Increase the number of GPUs requested in the job script to avoid using unconfigured GPUs.
      Correct
    • Option B:
      Check if MIG (Multi-Instance GPU) mode has been enabled incorrectly and reconfigure Slurm accordingly.
      Correct
    • Option C:
      Verify that non-MIG GPUs are automatically configured in Slurm when detected, and adjust configurations if needed.
      Correct
    • Option D:
      Ensure that GPU resource limits have been correctly defined in Slurm’s configuration file for each job type.
      Correct
    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer: B

    Explanation

    Comprehensive and Detailed Explanation From Exact Extract:
    Misconfiguration related to MIG mode can cause Slurm to improperly allocate GPUs, leading to job failures. The administrator should verify whether MIG has been enabled on the GPUs and ensure that Slurm’s configuration matches the hardware setup. If MIG is enabled, Slurm must be configured to recognize and schedule MIG partitions correctly to avoid resource conflicts.

  6. Question 6

    Single answer

    You are tasked with deploying a DOCA service on an NVIDIA BlueField DPU in an air-gapped data center environment. The DPU has the required BlueField OS version (3.9.0 or higher) installed, and you have access to the necessary container image from NVIDIA's NGC catalog. However, you need to ensure that the deployment process is successful without an internet connection.
    Which of the following steps should you take to deploy the DOCA service on the DPU?

    • Option A:
      Install Docker on the DPU, pull the container directly from NGC, and run it using ‘docker run’ with appropriate environment variables.
      Correct
    • Option B:
      Pull the container image from NGC using Docker and modify the YAML file before deployment.
      Correct
    • Option C:
      Manually download the container image and YAML file beforehand, transfer them to the DPU, and deploy using Kubernetes with standalone Kubelet.
      Correct
    • Option D:
      Use the host system’s Docker engine to pull the container image and deploy it on the DPU via SSH.
      Correct
    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer: C

    Explanation

    Comprehensive and Detailed Explanation From Exact Extract:
    In an air-gapped environment where the DPU has no internet connectivity, direct pulling of container images from NVIDIA’s NGC catalog is not possible. The recommended approach is to manually download the required container image and YAML deployment files from a connected system, then transfer these files to the DPU. Deployment is then performed using Kubernetes with a standalone Kubelet on the DPU, which can deploy the preloaded container image offline. This ensures the deployment proceeds successfully without internet access.

  7. Question 7

    Single answer

    A new researcher needs access to GPU resources but should not have permission to modify cluster settings or manage other users.
    What role should you assign them in Run:ai?

    • Option A:
      L1 Researcher
      Correct
    • Option B:
      Department Administrator
      Correct
    • Option C:
      Application Administrator
      Correct
    • Option D:
      Research Manager
      Correct
    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer: A

    Explanation

    Comprehensive and Detailed Explanation From Exact Extract:
    In Run:ai, roles are assigned based on levels of permissions. The L1 Researcher role is designed for users who need access to GPU resources for running jobs and experiments but should not have administrative rights over cluster settings or other users. This role ensures researchers can use resources without affecting cluster configurations or user management. Other roles like Department Administrator, Application Administrator, or Research Manager have broader privileges, including managing users and settings, which are not appropriate for the new researcher’s requirements.

  8. Question 8

    Single answer

    What is the primary purpose of assigning a provisioning role to a node in NVIDIA Base Command Manager (BCM)?

    • Option A:
      To configure the node as a container orchestration manager
      Correct
    • Option B:
      To enable the node to monitor GPU utilization across the cluster
      Correct
    • Option C:
      To allow the node to manage software images and provision other nodes
      Correct
    • Option D:
      To assign the node as a storage manager for certified storage
      Correct
    Show Answer & Explanation Hide Answer & Explanation

    Correct Answer: C

    Explanation

    Comprehensive and Detailed Explanation From Exact Extract:
    In NVIDIA Base Command Manager (BCM), assigning the provisioning role to a node enables that node to manage software images and perform provisioning tasks for other nodes in the cluster. This role allows automated deployment and configuration of cluster nodes, ensuring consistency and simplifying large-scale management. It is not primarily responsible for container orchestration, GPU monitoring, or storage management.