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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Security, Reliability, and Operations	15%	- Monitoring, logging, and troubleshooting AI environments - High availability and data protection - Cost management and efficiency - Data security and access control for AI
Topic 2: NetApp AI Solutions and Architecture	25%	- NetApp AI-ready infrastructure components - Scalability and performance optimization for AI - Storage architectures for AI workloads - ONTAP integration with AI frameworks - Data management and data pipeline design
Topic 3: AI Lifecycle	27%	- Predictive vs generative AI - Data preparation and management for AI - Model training, inference, and optimization - AI lifecycle stages: design, training, deployment, monitoring - AI governance, ethics, and compliance
Topic 4: Cloud and Hybrid Cloud AI Deployment	18%	- Hybrid and multi-cloud AI architectures - Data mobility and consistency across environments - NetApp cloud data services for AI - Cloud-native AI solutions and integration
Topic 5: AI Overview	15%	- Convergence of AI, high-performance computing, and analytics - AI industry use cases and applications - AI deployment models: on-premises, cloud, edge - Algorithm types: supervised, unsupervised, reinforcement learning - AI, machine learning, and deep learning concepts

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q20-Q25):

NEW QUESTION # 20
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. Provision a new, separate StorageGRID system and use BlueXP copy and sync to move the data.
B. Add new storage nodes to the existing StorageGRID system and execute an expansion procedure.
C. Replace the disks in the existing storage nodes with higher-capacity drives.
D. Use FabricPool to tier the excess data from StorageGRID to a public cloud provider.

Answer: B

NEW QUESTION # 21
An organization is developing a new AI-powered application. The initial phase involves feeding a curated 50 TB dataset of labeled images into a complex neural network, allowing the model to learn and adjust its internal parameters over millions of iterations. The second phase involves deploying this finalized model to a web service where it will process single, user-uploaded images and return a classification in real-time.
Which statement accurately describes these two phases?

A. Both Phase 1 and Phase 2 are examples of training.
B. Phase 1 is inferencing, and Phase 2 is training.
C. Phase 1 is training, and Phase 2 is inferencing.
D. Both Phase 1 and Phase 2 are examples of inferencing.

Answer: C

NEW QUESTION # 22
An architect is designing a data pipeline for a predictive AI model that will forecast retail sales.
The pipeline must be robust, version-controlled, and efficient.
The proposed data flow is as follows:
1. Ingest: Raw sales data is copied daily from multiple point-of-sale (POS) systems to a central staging area on an on-premises ONTAP cluster.
2. Prepare: The raw data is messy. A data engineering team needs a clean, isolated, and writable copy of the latest daily data to perform cleansing and feature engineering tasks without impacting the original raw data.
3. Train: Once prepared, the cleansed dataset is used to retrain the predictive model on a GPU cluster.
This step must be repeatable with the exact same dataset for compliance.
4. Deploy: The newly trained model is pushed to production inference servers.
Which combination of NetApp technologies best supports this entire predictive AI lifecycle?
(Select all
that apply.)

A. Use NetApp XCP to efficiently aggregate the raw sales data from POS systems into the central staging area.
B. Use NetApp StorageGRID as the primary storage for the high-performance training stage.
C. Use NetApp FlexClone to create an instantaneous, space-efficient, writable copy of the daily raw data for the data preparation stage.
D. Use NetApp Snapshots on the prepared dataset volume just before training to create an immutable, point-in-time version for compliance and reproducibility.
E. Use BlueXP backup and recovery to perform the initial data ingest from the POS systems.
F. Use a RAG architecture for the sales forecasting model.

Answer: A,C,D

NEW QUESTION # 23
The firm decides to expand the "Advisor Assistant" project to a new team in a different department. This team needs its own isolated environment. An MLOps engineer attempts to submit a new GPU- intensive job for the new team, but it remains pending. The engineer checks the Run:AI scheduler logs and finds the following entry:
time="2025-07-11T16:45:00Z" level=info msg="Job ds-new-team-job1 cannot be scheduled.
Project 'new-team-project' has exceeded its GPU quota. Quota: 0, Requested: 1, Used: 0." What is the root cause of the scheduling failure?

A. A Run:AI project quota has been configured for the new team, but it has been set to zero, effectively blocking them from using any GPU resources.
B. The Kubernetes cluster has no available GPUs.
C. The Run:AI scheduler is offline and cannot process new jobs.
D. The job is requesting a specific type of GPU that is not available in the cluster.

Answer: A

NEW QUESTION # 24
A junior administrator is attempting to delete an old, unused Snapshot copy from a production volume to reclaim space but receives an error. The administrator is certain they are using the correct command and have the appropriate 'vsadmin' role.
The command and error are shown below:
cluster-1::> volume snapshot delete -vserver svm_prod -volume app_data -snapshot nightly.2025- 06-15_0015 Error: command failed: This operation is not permitted. Deletion of Snapshot copy "nightly.2025-
06-15_0015" on volume "app_data" in Vserver "svm_prod" requires approval.
Use the "security multi-admin-verify approval show" command to view pending approvals.
What is the most likely reason the administrator cannot delete the Snapshot?

A. Multi-Admin Verification (MAV) is enabled, and the destructive operation requires approval from another designated administrator.
B. The 'vsadmin' role does not have permission to delete Snapshots.
C. The Snapshot is locked by a SnapMirror relationship.
D. The volume is protected by SnapLock, and the Snapshot has not reached its expiry date.

Answer: A

NEW QUESTION # 25
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