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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Objectives
Industry Use Cases	- AI applications across industries 1. Digital twins 2. Healthcare AI 3. Autonomous systems and agents
AI and Machine Learning Fundamentals	- Algorithm types 1. Unsupervised learning 2. Reinforcement learning 3. Supervised learning - AI, ML, DL concepts 1. Training, inference, and prediction workflows 2. Differences between AI, machine learning, and deep learning
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
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

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q84-Q89):

NEW QUESTION # 84
A university is building a shared AI research platform. They have two primary requirements:
1. Performance: A "hot" research area for active model training and development that requires the absolute lowest latency and highest throughput to support multiple, simultaneous GPU- intensive jobs.
The data in this area is around 50 TB.
2. Capacity & Cost: A "cold" data lake to store over 5 PB of raw, unstructured experimental data that is infrequently accessed but must be retained for compliance and future use. This tier must be as costeffective as possible.
Which combination of NetApp hardware and technologies should an architect select to build a complete, optimized, and cost-effective solution? (Select all that apply.)

A. Implement NetApp FabricPool to automatically tier inactive data from the ASA system to the StorageGRID data lake.
B. Use a NetApp All-SAN Array (ASA) system for the 50 TB high-performance "hot" research area.
C. Use NetApp E-Series systems for both the hot tier and the cold data lake to simplify management.
D. Use a standard 10GbE network for all connectivity to reduce costs.
E. Use NetApp StorageGRID to build the 5 PB cost-effective data lake.
F. Enable GPUDirect Storage on the ASA system to provide the lowest latency data path to the GPUs.

Answer: A,B,E,F

NEW QUESTION # 85
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 core ONTAP filer is using slow, capacity-based disks.
B. The model file is being transferred over a slow, high-latency WAN link for every load request.
C. The NFS version used between the core and edge is outdated.
D. The edge server does not have enough RAM to cache the model effectively.

Answer: B

NEW QUESTION # 86
Which of the following describes the impact of generative AI in content creation?

A. Generative AI analyzes data without generating content.
B. Generative AI only processes pre-existing content.
C. Generative AI predicts customer preferences without creating new content.
D. Generative AI can create new content such as text, images, and videos.

Answer: D

NEW QUESTION # 87
To comply with the security mandate, the architect must design a process to prevent client PII from the portfolio database from ever being included in the context sent to the LLM. Which two actions are required to build a robust and automated solution for this? (Choose 2.)

A. Move the entire client portfolio database to an encrypted, air-gapped system.
B. Use BlueXP classification to perform an initial scan of the portfolio database to identify and tag all columns containing PII.
C. Rely on a disclaimer in the chatbot UI telling advisors not to enter queries related to specific clients.
D. Implement a data preparation step in the RAG pipeline that programmatically masks or excludes any data fields tagged as PII before the context is constructed.
E. Fine-tune the LLM on a sanitized dataset to teach it to ignore PII.

Answer: B,D

NEW QUESTION # 88
The company decides to establish a disaster recovery (DR) site in a secondary data center for the entire Digital Twin platform. The DR plan must protect the HPC data, the AI training data, and the central data lake.
The DR requirements are:
- RPO: 4 hours for all data.
- RTO: 24 hours for the entire platform.
- Process: The failover and failback process should be as automated as possible.
Which combination of technologies provides the most comprehensive DR solution?

A. Use NetApp SnapMirror for the ASA, StorageGRID's built-in replication for the data lake, and a host- based tool like 'rsync' for the E-Series/BeeGFS data, all orchestrated via BlueXP disaster recovery.
B. Use BlueXP backup and recovery to back up all three storage systems (ASA, E-Series, StorageGRID) to a single cloud target.
C. Use NetApp SnapMirror for the ASA, StorageGRID replication for the data lake, and rely on tape backups for the E-Series/BeeGFS data.
D. Deploy a MetroCluster configuration spanning the primary and DR sites for all three storage systems.

Answer: A

NEW QUESTION # 89
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