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NVIDIA NCA-AIIO Exam Syllabus Topics:

TopicDetails
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
  • 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.
Topic 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.

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

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NVIDIA-Certified Associate AI Infrastructure and Operations Sample Questions:

What factor has led to the rapid increase and adoption of AI?

  • A. The efficient use of large amounts of data to train models.
  • B. Standard software integration between CPUs and GPUs.
  • C. The adoption of software libraries for portability.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Which metric is LEAST appropriate for evaluating recommendation ranking quality?

  • A. MAP
  • B. Precision@K
  • C. NDCG
  • D. Accuracy
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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In a data center, what is the purpose and benefit of a DPU?

  • A. A DPU is responsible for providing backup and disaster recovery solutions.
  • B. A DPU is designed to offload, accelerate, and isolate infrastructure workloads.
  • C. A DPU is used for managing physical infrastructure, such as power and cooling.
  • D. A DPU is responsible for managing network connections and security.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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An AI system is deployed to detect when people enter a restricted area using multiple IP cameras. Which AI use case is being exercised?

  • A. Signal Processing
  • B. Video Surveillance
  • C. Intelligent Video Analytics
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

Explanation: Only visible for 2Pass4sure members. You can sign-up / login (it's free).

Which NVIDIA tool aids data center monitoring and management?

  • A. NVIDIA DCGM
  • B. NVIDIA TensorRT
  • C. NVIDIA Mellanox Insight
  • D. NVIDIA Clara
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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