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Network Appliance NS0-901 Exam Syllabus Topics:

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

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q91-Q96):

NEW QUESTION # 91
A training job on one of the NVIDIA DGX servers is running slowly. A performance engineer runs the 'dstat' command on the server and captures the following output during the job execution.
-total-cpu-usage- -dsk/total- -net/total- paging-- system-- usr sys idl wai hiq siq| read writ| recv send| in out | int csw 15 5 70 10 0 0| 1.2G 15.0M| 1.2G 12.0M| 0 0 | 15k 35k
14 6 69 11 0 0| 1.2G 14.3M| 1.2G 11.8M| 0 0 | 14k 33k
16 5 68 11 0 0| 1.2G 16.1M| 1.2G 13.1M| 0 0 | 16k 36k
The server is connected to the NetApp ASA via a 100GbE (12.5 GB/s) network.
What is the most likely performance bottleneck based on this data?

A. The server's network interface is saturated.
B. The application is experiencing excessive memory paging.
C. The storage system (ASA) is unable to provide sufficient read throughput.
D. The server's CPU is overloaded.

Answer: A

NEW QUESTION # 92
The firm has acquired a competitor, and the volume of proprietary documents for the "Advisor Assistant" is expected to triple, exceeding the capacity of the current StorageGRID data lake. The architect needs to expand the data lake's capacity non-disruptively.
The current StorageGRID status is:
System_Health: Nominal
Node_Count: 6 (3 Storage Nodes, 3 Admin/Gateway Nodes)
Usable_Capacity: 1.5 PB
Used_Capacity: 1.4 PB (93%)
What is the standard procedure for scaling the capacity of the on-premises NetApp StorageGRID system?

A. Replace the disks in the existing storage nodes with higher-capacity drives.
B. Add new storage nodes to the existing StorageGRID system and execute an expansion procedure.
C. Provision a new, separate StorageGRID system and use BlueXP copy and sync to move the data.
D. Use FabricPool to tier the excess data from StorageGRID to a public cloud provider.

Answer: B

NEW QUESTION # 93
An organization has a core data center with a large AI training cluster and several remote edge locations for data ingest and local inference. The edge locations frequently need access to the latest models trained in the core data center, but WAN bandwidth is limited and can be unreliable.
Users at the edge are reporting slow model loading times.
An architect reviews the data access logs from an edge site:
Timestamp: 2025-07-11T15:30:00Z
Event: Model_Load_Request
Model_Path: nfs://core-filer.example.com/vol/models/latest_model.pkl
Source_IP: 192.168.100.15 (Edge Server)
Destination_IP: 10.1.1.50 (Core Filer)
Status: SUCCESS
Duration: 3600s (60 minutes)
What is the most likely cause of the slow model loading times at the edge?

A. The NFS version used between the core and edge is outdated.
B. The edge server does not have enough RAM to cache the model effectively.
C. The model file is being transferred over a slow, high-latency WAN link for every load request.
D. The core ONTAP filer is using slow, capacity-based disks.

Answer: C

NEW QUESTION # 94
A distributed training job running on the AIPod fails to start. The MLOps engineer inspects the events for one of the pending training pods and sees the following message:
Events:
Type Reason Age From Message
- - - -
Warning FailedScheduling 5m12s default-scheduler 0/4 nodes are available: 4 node(s) had no available volume zone.
The PersistentVolumeClaim (PVC) for this pod specifies a StorageClass that uses the 'ontap-nas' Trident provisioner.
he Trident logs show no errors.
What is the most likely cause of this scheduling failure?

A. The NetApp ASA storage system is offline.
B. The 'requiredTopology' in the StorageClass is misconfigured, preventing Trident from finding a valid ONTAP backend in the same zone as the available compute nodes.
C. The Kubernetes nodes do not have the necessary NFS client utilities installed.
D. The training pod's container image does not exist in the registry.

Answer: B

NEW QUESTION # 95
An AI architect needs to design a complete, end-to-end data pipeline for a new generative AI application at a financial services firm. The application will allow internal analysts to query a massive, 500 TB archive of historical market data and reports to generate summaries. The firm has the following environment and requirements:
Data_Sources: A mix of on-premises ONTAP filers and StorageGRID S3 buckets.
Requirement_1: All queries must be answered using only the private data archive.
Requirement_2: All generated summaries must provide citations to the source reports.
Requirement_3: All data containing client PII must be identified and excluded from the LLM context.
Requirement_4: The solution must be cost-effective for the large, mostly-read data archive.
Which set of actions and technologies constitutes the most robust and compliant solution?
(Select all that apply.)

A. Use NetApp XCP to perform a one-time migration of all data from the ONTAP filers to the StorageGRID data lake.
B. Fine-tune a foundation model on the entire 500 TB dataset to ensure it understands the financial context.
C. Use SnapMirror to replicate the StorageGRID data lake to a high-performance NetApp ASA system for faster query performance.
D. During the RAG retrieval step, filter out any documents tagged as containing PII by BlueXP classification before sending them to the LLM.
E. Deploy BlueXP classification to scan the entire StorageGRID data lake to identify and tag all files containing PII.
F. Implement a Retrieval-Augmented Generation (RAG) architecture to meet the requirements for private data usage and source citation.

Answer: A,D,E,F

NEW QUESTION # 96
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