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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Objectives
AI Lifecycle and Deployment	- End-to-end AI lifecycle 1. Data ingestion and preparation 2. Model training and validation 3. Model deployment and monitoring - Operational challenges 1. Scalability and performance optimization 2. Data governance and management
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. Supervised learning 2. Reinforcement learning 3. Unsupervised learning
Industry Use Cases	- AI applications across industries 1. Digital twins 2. Healthcare AI 3. Autonomous systems and agents
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. AI, HPC, and analytics convergence 2. Shared infrastructure design considerations

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q50-Q55):

NEW QUESTION # 50
In the data pipeline, which NetApp technology is used to create an efficient, block-level, incremental replication of the anonymized datasets from the on-premises ASA to the Cloud Volumes ONTAP instance in Azure?

A. NetApp XCP
B. NetApp SnapMirror
C. NetApp FabricPool
D. NetApp BlueXP copy and sync

Answer: B

NEW QUESTION # 51
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 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.
D. Create a new StorageGRID tenant account for the auditors with full S3 access.

Answer: C

NEW QUESTION # 52
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 Run:AI scheduler is offline and cannot process new jobs.
C. The job is requesting a specific type of GPU that is not available in the cluster.
D. The Kubernetes cluster has no available GPUs.

Answer: A

NEW QUESTION # 53
An architect is designing the storage and network infrastructure for a new, large-scale AI cluster dedicated to training foundational models. The primary design goal is to achieve the highest possible data throughput and the lowest latency to ensure multi-million dollar GPU resources are never idle. Which two technologies are essential to include in the design to achieve this goal?
(Choose 2.)

A. A tiered storage architecture using NetApp FabricPool.
B. An InfiniBand or RoCE-capable Ethernet network fabric.
C. GPUDirect Storage support on the storage system.
D. A 10GbE Ethernet network for all data traffic.
E. NetApp StorageGRID as the primary storage for the training datasets.

Answer: B,C

NEW QUESTION # 54
A national research laboratory is investing in a turnkey AI infrastructure solution. Their primary goal is to eliminate the complexity and risk of designing and integrating the compute, network, and storage components themselves. The solution must be pre-validated by the vendors to deliver predictable, linear performance as they scale from one to multiple compute nodes. Which two options represent this type of pre-validated, converged infrastructure solution for AI? (Choose two)

A. A single NetApp FAS system connected directly to a single server.
B. A custom-built server rack with components sourced from various different vendors.
C. NetApp AIPod, which integrates NVIDIA DGX servers with NetApp storage and networking.
D. A Cisco and NetApp FlexPod for AI solution.
E. A public cloud provider's general-purpose virtual machine instances.

Answer: C,D

NEW QUESTION # 55
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