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Exam Code: NCA-AIIO

Exam Name: NVIDIA-Certified Associate AI Infrastructure and Operations

Updated: Oct 12, 2026

Number: 125 Q&As with Testing Engine

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NVIDIA NCA-AIIO Exam Overview:

Certification Vendor:	NVIDIA
Exam Name:	NVIDIA-Certified Associate AI Infrastructure and Operations (NCA-AIIO)
Exam Number:	NCA-AIIO
Exam Duration:	90 minutes
Certificate Validity Period:	2 years
Related Certifications:	NVIDIA-Certified Professional (various tracks) NVIDIA-Certified Associate: Generative AI LLMs
Available Languages:	English
Exam Format:	Multiple select, Multiple choice
Recommended Training:	NVIDIA Deep Learning Institute (DLI)
Exam Registration:	NVIDIA Certification Portal
Sample Questions:	NVIDIA NCA-AIIO Sample Questions
Exam Way:	Online proctored exam (remote), typically delivered via authorized certification platform
Pre Condition:	No formal prerequisites required; recommended familiarity with basic AI/ML concepts and IT infrastructure.
Official Syllabus URL:	https://www.nvidia.com/en-us/training/certification/

NVIDIA NCA-AIIO Exam Syllabus Topics:

Topic	Details
Topic 1	AI Infrastructure: This section of the exam measures the skills of IT professionals and focuses on the physical and architectural components needed for AI. It involves understanding the process of extracting insights from large datasets through data mining and visualization. Candidates must be able to compare models using statistical metrics and identify data trends. The infrastructure knowledge extends to data center platforms, energy-efficient computing, networking for AI, and the role of technologies like NVIDIA DPUs in transforming data centers.
Topic 2	AI Operations: This section of the exam measures the skills of data center operators and encompasses the management of AI environments. It requires describing essentials for AI data center management, monitoring, and cluster orchestration. Key topics include articulating measures for monitoring GPUs, understanding job scheduling, and identifying considerations for virtualizing accelerated infrastructure. The operational knowledge also covers tools for orchestration and the principles of MLOps.
Topic 3	Essential AI knowledge: Exam Weight: This section of the exam measures the skills of IT professionals and covers foundational AI concepts. It includes understanding the NVIDIA software stack, differentiating between AI, machine learning, and deep learning, and comparing training versus inference. Key topics also involve explaining the factors behind AI's rapid adoption, identifying major AI use cases across industries, and describing the purpose of various NVIDIA solutions. The section requires knowledge of the software components in the AI development lifecycle and an ability to contrast GPU and CPU architectures.

Reference: https://www.nvidia.com/en-us/learn/certification/ai-infrastructure-operations-associate/

NVIDIA-Certified Associate AI Infrastructure and Operations Sample Questions:

Question #1
What is an advantage of InfiniBand over Ethernet?

A. InfiniBand always provides higher bandwidth than Ethernet.
B. InfiniBand offers lower latency than Ethernet.
C. InfiniBand supports RDMA while Ethernet does not.

Question #2
Which characteristic best describes inference when comparing inference to deep learning training?

A. Inference has larger data requirements.
B. Inference requires smaller amounts of hardware.
C. Inference takes longer to evaluate.

Question #3
How many distinct network fabrics are in an AI cluster?

A. 5
B. 2
C. 3
D. 4

Question #4
A company is implementing a new network architecture and needs to consider the requirements and considerations for training and inference. Which of the following statements is true about training and inference architecture?

A. Training architecture and inference architecture cannot be the same.
B. Training architecture is focused on optimizing performance while inference architecture is focused on reducing latency.
C. Training architecture is only concerned with hardware requirements, while inference architecture is only concerned with software requirements.
D. Training architecture and inference architecture have the same requirements and considerations.

Question #5
Which network provides the optimal performance for multi-node AI training workloads?

A. InfiniBand
B. Software Defined Network (SDN)
C. Fibre Channel

Solutions:

Question #1
Correct Answer: B

Question #2
Correct Answer: B

Question #3
Correct Answer: C

Question #4
Correct Answer: B

Question #5
Correct Answer: A

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