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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

1. The architect is designing the complete, automated data pipeline from the on-premises data center to the Azure cloud for this medical imaging project. The design must prioritize security, efficiency, and reproducibility.
Which sequence of actions provides the most robust and automated solution?

A) Use BlueXP classification to scan the on-prem data; use a DataOps Toolkit script to trigger a FlexClone of the source volume for anonymization; use SnapMirror to replicate the anonymized clone to Cloud Volumes ONTAP; then begin training in Azure.
B) Use SnapMirror to replicate the raw, sensitive data to Azure first, then run BlueXP classification in the cloud to find PII.
C) Use FabricPool to automatically tier all raw data to Azure Blob storage, then mount the blob container to the training VMs.
D) Manually copy raw data to Azure, run a cloud-based script to anonymize it, then start training.

2. An automotive company runs crash simulations on a dedicated High-Performance Computing (HPC) cluster and trains computer vision models on a separate AI cluster. Data scientists are complaining about the long delays required to move terabytes of simulation output data from the HPC storage to the AI cluster's storage before they can begin training.
The current data flow is as follows:
HPC Cluster -> --Manual Copy (NFS)--> -> AI Cluster
An architect has been asked to redesign the infrastructure to eliminate this data movement bottleneck.
Which architectural change would be most effective?

A) Implement a converged data infrastructure where both the HPC and AI clusters access a single, high- performance data lake built on NetApp storage.
B) Install faster CPUs in the AI cluster's storage controllers.
C) Use NetApp XCP to perform the data copy, as it is faster than a standard NFS copy.
D) Upgrade the network connection between the two storage systems to 200GbE.

3. Which of the following describes the impact of generative AI in content creation?

A) Generative AI predicts customer preferences without creating new content.
B) Generative AI analyzes data without generating content.
C) Generative AI can create new content such as text, images, and videos.
D) Generative AI only processes pre-existing content.

4. A robotics company is developing a control system for an autonomous warehouse drone. The drone must learn to navigate complex environments to pick up packages. The development team has created a physics-based simulation where the drone can attempt the task millions of times.
The drone receives a positive reward for successfully retrieving a package and a negative penalty for collisions. Which type of machine learning algorithm is being used in this scenario?

A) Unsupervised learning
B) Generative learning
C) Reinforcement learning
D) Supervised learning

5. An AI infrastructure engineer is troubleshooting a poorly performing distributed training job. The job is running across multiple nodes, each equipped with powerful GPUs. The engineer observes that overall GPU utilization is unexpectedly low. System-level monitoring on the compute nodes provides the following metrics during a training run.
avg_gpu_utilization: 25%
avg_cpu_iowait_percent: 65%
avg_network_bandwidth_util: 95% (on a 10GbE network)
storage_array_latency: <1ms
Given these metrics, what is the most likely bottleneck causing the low GPU utilization?

A) The network connecting the compute nodes and storage is saturated and has become the primary bottleneck.
B) The GPUs are faulty and cannot process data at their rated speed.
C) The storage array is too slow and cannot serve data quickly enough.
D) The CPU is underpowered and cannot preprocess the data fast enough for the GPUs.

Solutions: