NCA-AIIO Exam Preparation Material | AI Infrastructure and Operations

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Prepare for the NCA-AIIO AI Infrastructure and Operations exam with CertQueen's independently developed study resources. Review important concepts, practice scenario-based questions, and use clear explanations to identify areas that require further study.

Question#1

The foundation of the NVIDIA software stack is the DGX OS.
Which of the following Linux distributions is DGX OS built upon?

A. Ubuntu
B. Red Hat
C. CentOS

Explanation:
DGX OS, the operating system powering NVIDIA DGX systems, is built on Ubuntu Linux, specifically the Long-Term Support (LTS) version. It integrates Ubuntu’s robust base with NVIDIA-specific enhancements, including GPU drivers, tools, and optimizations tailored for AI and high-performance computing workloads. Neither Red Hat nor CentOS serves as the foundation for DGX OS, making Ubuntu the correct choice.
(Reference: NVIDIA DGX OS Documentation, System Requirements Section)

Question#2

A company is deploying a large-scale AI training workload that requires distributed computing across multiple GPUs. They need to ensure efficient communication between GPUs on different nodes and optimize the training time.
Which of the following NVIDIA technologies should they use to achieve this?

A. NVIDIA NVLink
B. NVIDIA NCCL (NVIDIA Collective Communication Library)
C. NVIDIA DeepStream SDK
D. NVIDIA TensorRT

Question#3

You are responsible for deploying a deep learning model for image recognition across a global network of autonomous vehicles. The model requires real-time inference and must be updated frequently with new training data. The deployment needs to be highly efficient in both edge and cloud environments, with minimal latency.
Which combination of NVIDIA technologies would best meet the requirements for this deployment?

A. Use NVIDIA Jetson AGX Xavier for edge inference and NVIDIA Fleet Command for centralized management.
B. Use NVIDIA Quadro RTX GPUs on each vehicle for real-time inference.
C. Utilize NVIDIA Tesla V100 GPUs in the cloud with TensorRT for optimized inference.
D. Deploy the model on NVIDIA DGX systems located in data centers for real-time inference.

Question#4

A financial institution is deploying two different machine learning models to predict credit defaults. The models are evaluated using Mean Squared Error (MSE) as the primary metric. Model A has an MSE of 0.015, while Model B has an MSE of 0.027. Additionally, the institution is considering the complexity and interpretability of the models. Given this information, which model should be preferred and why?

A. Model A should be preferred because it is more interpretable than Model
B. Model A should be preferred because it has a lower MSE, indicating better performance.
C. Model B should be preferred because it has a higher MSE, indicating it is less likely to overfit.
D. Model A should be preferred because it has a more complex architecture, leading to better long- term performance.

Question#5

What is a key consideration when virtualizing accelerated infrastructure to support AI workloads on a hypervisor-based environment?

A. Ensure GPU passthrough is configured correctly.
B. Disable GPU overcommitment in the hypervisor.
C. Enable vCPU pinning to specific cores.
D. Maximize the number of VMs per physical server.

Exam CodeNCA-AIIO
Q & A: 107 Q&As         Updated:  Sep 21,2026

 

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Review Key Concepts

Review the technologies, products, processes, and practical skills covered by the current NCA-AIIO exam objectives.

Practice Scenario-Based Questions

Work through independently developed questions designed to strengthen your understanding of technical scenarios and decision-making.

Identify Knowledge Gaps

Use your results and the provided explanations to find weaker areas and focus your study more effectively.

How to Use This NCA-AIIO Preparation Material

Review the Exam Scope

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Study the Explanations

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Close Knowledge Gaps

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