NVIDIA NCA-AIIO 考試大綱：

主題	簡介
主題 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.
主題 2	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.
主題 3	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.

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

NVIDIA NCA-AIIO 考試概覽:

認證廠商:	NVIDIA
考試名稱:	NVIDIA 認證助理級人工智慧基礎架構與營運專業人員
考試代碼:	NCA-AIIO
支援語言:	English
考試時間:	60 分鐘
考試形式:	模擬類型題目, 情境導向題目, 選擇題
實際考試題數:	50
證照有效期限:	2 年
考試費用:	125 美元
相關認證:	NVIDIA-Certified Associate
範例考題:	NVIDIA NCA-AIIO 範例考題
考試方式:	線上考試，由 Certiverse 提供遠端監考服務
必備條件:	具備資料中心基礎架構的基礎知識
官方大綱網址:	https://www.nvidia.com/en-us/learn/certification/ai-infrastructure-operations-associate

最新的 NVIDIA-Certified Associate NCA-AIIO 免費考試真題：

問題 #1

What distinguishes GPU architecture from CPU architecture?

A. CPUs lack memory bandwidth.
B. GPUs have thousands of smaller cores for parallel tasks.
C. CPUs have more cores than GPUs.
D. GPUs prioritize single-threaded performance.

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答案：B 🗳️

說明：（僅 VCESoft 成員可見）

問題 #2

What is the maximum number of MIG instances that an H100 GPU provides?

A. 7
B. 4
C. 8

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答案：A 🗳️

說明：（僅 VCESoft 成員可見）

問題 #3

When should RoCE be considered to enhance network performance in a multi-node AI computing environment?

A. A network with large amounts of storage traffic.
B. A network that cannot utilize the full available bandwidth due to high CPU utilization.
C. A network that experiences a high packet loss rate (PLR).

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答案：B 🗳️

說明：（僅 VCESoft 成員可見）

問題 #4

What is the benefit of Kubernetes in application deployments in an AI environment?

A. It simplifies deployment and directly improves the accuracy of AI models by optimizing their hyperparameters.
B. It simplifies deployment through automation of AI algorithms for machine learning models.
C. It improves scaling through enhancement of the computational power of GPUs used in AI workloads.
D. It improves scaling of applications by allowing for automated replication and load balancing of containers.

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答案：D 🗳️

說明：（僅 VCESoft 成員可見）

問題 #5

When deploying high-density workloads in a data center, what are the three main resource constraints that need to be considered?