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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Objectives
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
AI and Machine Learning Fundamentals	- Algorithm types 1. Unsupervised learning 2. Supervised learning 3. Reinforcement learning - AI, ML, DL concepts 1. Differences between AI, machine learning, and deep learning 2. Training, inference, and prediction workflows
AI Lifecycle and Deployment	- Operational challenges 1. Data governance and management 2. Scalability and performance optimization - End-to-end AI lifecycle 1. Model deployment and monitoring 2. Model training and validation 3. Data ingestion and preparation
Industry Use Cases	- AI applications across industries 1. Healthcare AI 2. Digital twins 3. Autonomous systems and agents

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q60-Q65):

NEW QUESTION # 60
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. 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.
B. Create a new StorageGRID tenant account for the auditors with full S3 access.
C. Configure an NFS export policy on the 'prod-docs' bucket and provide the auditors with the mount path.
D. Provide the auditors with the root access keys for the StorageGRID system.

Answer: A

A. Project A requires only a large amount of data, while Project B requires only a large amount of code.
B. Both projects are examples of fine-tuning and have similar infrastructure needs.
C. Project B is a fine-tuning task, which leverages an existing model and requires less data and compute resources than building a model from scratch.
D. Both projects should use NetApp StorageGRID as the primary storage for training to ensure low latency.
E. Project A is a model building task and requires a significantly larger and more powerful compute and storage infrastructure than Project B.

Answer: C,E

NEW QUESTION # 62
An organization's AI platform team needs to provide two distinct tiers of storage for their data scientists on a single Kubernetes cluster:
1. 'gold-tier': Extremely low-latency storage for active model training, using an all-flash NetApp ASA system.
2. 'bronze-tier': Cost-effective, high-capacity storage for data staging and archiving, using a NetApp StorageGRID system.
How should the platform team configure NetApp Trident to meet these requirements? (Select all that apply.)

A. Configure the 'gold-tier' StorageClass to reference the ASA backend.
B. Create a single Trident backend that points to both the ASA and StorageGRID systems simultaneously.
C. Create two separate Trident backend configurations, one for the ASA ('backend-asa.yaml') and one for StorageGRID ('backend-sgrid.yaml').
D. Configure the 'bronze-tier' StorageClass to reference the StorageGRID backend.
E. Create two distinct StorageClasses, 'gold-tier' and 'bronze-tier'.
F. Create a single StorageClass named 'multi-tier-storage' that references both backends.

Answer: A,C,D,E

NEW QUESTION # 63
The firm wants to extend the "Advisor Assistant" to include a new batch processing feature. Every night, the system must analyze every client portfolio against a set of 50 different risk models and generate a compliance report. This is a highly parallel, read-intensive workload. The architect must design a data workflow that is efficient and does not impact the production chatbot environment. Which sequence of actions and technologies provides the most effective solution?

A. Create a NetApp Snapshot of the portfolio database volume, create a FlexClone from that snapshot, mount the FlexClone to the analysis pods, and run the batch job.
B. Use NetApp SnapMirror to replicate the portfolio database volume to the DR site, and run the analysis jobs there.
C. Run the analysis job directly against the production portfolio database during off-peak hours.
D. Create a full physical copy of the client portfolio database to a separate volume, mount it to the compute nodes, and run the analysis.

Answer: A

NEW QUESTION # 64
An AI operations team is troubleshooting why their RAG-based chatbot is providing outdated information. They have confirmed that the vector database embedding process is functioning correctly, but suspect an issue with the initial data synchronization that moves the knowledge base from an on- premises ONTAP file share to a cloud staging bucket.
They inspect the relevant BlueXP copy and sync job and find the following details:
Service: BlueXP copy and sync
Relationship_Name: KB_Sync_to_Vector_Staging
Source: nfs://ontap-cluster-1/vol_kb/docs
Destination: s3://vector-staging-bucket-89a3/latest/
Last_Sync_Status: FAILED
Last_Sync_Time: 2025-07-11T02:00:15Z
Error_Message: "Authentication error:
Unable to access source.
Check export policy on 'vol_kb'."
Based on this information, what is the most direct solution to fix the data pipeline?

A. Fine-tune the LLM with the latest data instead of using the RAG system.
B. Re-run the vector database embedding job.
C. Check the IAM permissions for the role associated with the S3 bucket.
D. Modify the NFS export policy on the 'vol_kb' volume on the on-premises ONTAP cluster to grant access to the BlueXP Connector.

Answer: D

NEW QUESTION # 65
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