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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Objectives
Topic 1: AI Lifecycle and Deployment	- End-to-end AI lifecycle 1. Model deployment and monitoring 2. Model training and validation 3. Data ingestion and preparation - Operational challenges 1. Data governance and management 2. Scalability and performance optimization
Topic 2: Industry Use Cases	- AI applications across industries 1. Digital twins 2. Autonomous systems and agents 3. Healthcare AI
Topic 3: AI Infrastructure and NetApp Solutions	- Converged workloads 1. AI, HPC, and analytics convergence 2. Shared infrastructure design considerations - AI-ready data infrastructure 1. Data pipeline optimization for AI/ML workloads 2. High-performance storage for AI workloads
Topic 4: AI and Machine Learning Fundamentals	- Algorithm types 1. Supervised learning 2. Unsupervised learning 3. Reinforcement learning - AI, ML, DL concepts 1. Training, inference, and prediction workflows 2. Differences between AI, machine learning, and deep learning

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q71-Q76):

NEW QUESTION # 71
A data scientist is using the NetApp DataOps Toolkit for Python to automate the creation of a new, writable volume for an experiment. The script is intended to clone an existing dataset volume. When the script is executed, it fails with an error.
The relevant portion of the Python script is:
from netapp_dataops.k8s import clone_pvc
clone_pvc(
source_pvc_name="dataset-v1-pvc",
new_pvc_name="experiment-clone-pvc",
namespace="ds-team-1"
)
The script produces the following error in the terminal:
'Error: Failed to clone PVC. Source PVC 'dataset-v1-pvc' not found in namespace 'ds-team-1'.' What is the most likely cause of this error?

A. The NetApp DataOps Toolkit does not support cloning volumes.
B. The Python script is missing the necessary import statement for the toolkit.
C. The Kubernetes cluster does not have NetApp Trident installed.
D. The source PersistentVolumeClaim (PVC) named 'dataset-v1-pvc' does not exist or is in a different namespace.

Answer: D

NEW QUESTION # 72
A new team of external auditors requires read-only access to the raw financial product documentation stored in the StorageGRID data lake. The data is in a bucket named 'prod-docs'.
The security team must ensure the auditors can list and read objects but cannot write, delete, or modify any data. Which is the most appropriate method to grant this specific access?

A. Provide the auditors with the root access keys for the StorageGRID system.
B. Configure an NFS export policy on the 'prod-docs' bucket and provide the auditors with the mount path.
C. Create a new StorageGRID tenant account for the auditors with full S3 access.
D. Create a new group and user within StorageGRID, and attach an S3 group policy that explicitly allows only 's3:GetObject' and 's3:ListBucket' actions on the 'prod-docs' bucket.

Answer: D

NEW QUESTION # 73
The HPC cluster generates simulation data at an extremely high rate, requiring a storage system that can handle massively parallel writes from hundreds of compute nodes simultaneously. Which storage system and file protocol combination is the most appropriate choice for the HPC cluster's high-performance scratch space?

A. A NetApp ASA system serving a single, large NFS volume.
B. A NetApp StorageGRID system accessed via the S3 protocol.
C. A Cloud Volumes ONTAP instance with a standard file system.
D. A NetApp E-Series system serving a BeeGFS parallel file system.

Answer: D

NEW QUESTION # 74
An AI platform is suffering from poor performance during distributed training jobs. The training data resides on a single, large NFS volume. Monitoring shows that while the overall network throughput to the storage system is high, individual GPU nodes experience significant I/O wait times, and the single ONTAP volume is becoming a performance bottleneck. The goal is to re- architect the storage layout to maximize read parallelism and throughput for the training cluster.
Which two actions should the architect take to address this performance bottleneck? (Choose 2.)

A. Replace the NFS protocol with iSCSI for all training data access.
B. Implement a NetApp FlexGroup volume to spread the dataset across multiple constituent volumes and aggregates.
C. Enable QoS maximums on the training volume to limit its IOPS.
D. Use NetApp FlexCache to create a local cache of the training data on each compute node.
E. Increase the number of network ports connected to the storage controller.

Answer: B,D

NEW QUESTION # 75
The data scientists report that their Kubernetes-based data preparation jobs are failing. The pods are stuck in a 'Pending' state.
An MLOps engineer runs 'kubectl describe pvc data-prep-pvc-01' and sees the following event:
Type Reason Age From Message
- - - -
Warning ProvisioningFailed 2m15s trident-orchestrator-7b... failed to provision volume with StorageClass "bronze-tier": backend unavailable: no healthy backend with satisfying attributes for storage class "bronze-tier" The engineer checks the Trident backend configurations and finds no backend associated with the "bronze-tier" StorageClass.
What is the root cause of the failure?

A. The StorageGRID data lake is offline, preventing the creation of new volumes.
B. The Kubernetes scheduler is unable to find a node with enough resources for the pods.
C. The data preparation pods do not have the correct security permissions.
D. The PersistentVolumeClaim is referencing a StorageClass that has no configured or healthy Trident backend to provision storage from.

Answer: D

NEW QUESTION # 76
......

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