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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Objectives
Topic 1: Industry Use Cases	- AI applications across industries 1. Healthcare AI 2. Autonomous systems and agents 3. Digital twins
Topic 2: AI and Machine Learning Fundamentals	- AI, ML, DL concepts 1. Training, inference, and prediction workflows 2. Differences between AI, machine learning, and deep learning - Algorithm types 1. Unsupervised learning 2. Supervised learning 3. Reinforcement learning
Topic 3: AI Lifecycle and Deployment	- Operational challenges 1. Data governance and management 2. Scalability and performance optimization - End-to-end AI lifecycle 1. Data ingestion and preparation 2. Model training and validation 3. Model deployment and monitoring
Topic 4: AI Infrastructure and NetApp Solutions	- Converged workloads 1. Shared infrastructure design considerations 2. AI, HPC, and analytics convergence - 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 (Q34-Q39):

NEW QUESTION # 34
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. Configure an NFS export policy on the 'prod-docs' bucket and provide the auditors with the mount path.
B. 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.
C. Create a new StorageGRID tenant account for the auditors with full S3 access.
D. Provide the auditors with the root access keys for the StorageGRID system.

Answer: B

NEW QUESTION # 35
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. Enable GPUDirect Storage on the ASA system to provide the lowest latency data path to the GPUs.
C. Use NetApp E-Series systems for both the hot tier and the cold data lake to simplify management.
D. Use a NetApp All-SAN Array (ASA) system for the 50 TB high-performance "hot" research area.
E. Use NetApp StorageGRID to build the 5 PB cost-effective data lake.
F. Use a standard 10GbE network for all connectivity to reduce costs.

Answer: A,B,D,E

NEW QUESTION # 36
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 StorageGRID as the primary storage for the high-performance training stage.
B. Use BlueXP backup and recovery to perform the initial data ingest from the POS systems.
C. Use NetApp XCP to efficiently aggregate the raw sales data from POS systems into the central staging area.
D. Use a RAG architecture for the sales forecasting model.
E. Use NetApp FlexClone to create an instantaneous, space-efficient, writable copy of the daily raw data for the data preparation stage.
F. Use NetApp Snapshots on the prepared dataset volume just before training to create an immutable, point-in-time version for compliance and reproducibility.

Answer: C,E,F

NEW QUESTION # 37
An AI architect is reviewing the design for a new data lake. The primary requirement is to store petabytes of unstructured data (images, video, sensor logs) in a highly durable, scalable, and cost- effective manner. The data will be accessed via S3 API by various data processing and analytics applications.
The initial design proposes using a traditional Network Attached Storage (NAS) filer with a large number of disks. The architect reviews the proposal:
Proposed_System: Traditional NAS Filer
Protocol: NFSv4
Scalability_Model: Scale-up
Metadata_Handling: Centralized in filer head
Cost_per_GB: Moderate
Why is this proposed system a poor choice for a petabyte-scale data lake?

A. A traditional scale-up NAS system will face scalability and cost-effectiveness challenges at the petabyte scale compared to an object storage system.
B. A NAS filer cannot be deployed on-premises.
C. The S3 API cannot be used to access data stored on an NFS file system.
D. NFS is incapable of storing image or video files.

Answer: A

NEW QUESTION # 38
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. Configure the 'bronze-tier' StorageClass to reference the StorageGRID backend.
C. Create a single StorageClass named 'multi-tier-storage' that references both backends.
D. Create a single Trident backend that points to both the ASA and StorageGRID systems simultaneously.
E. Create two separate Trident backend configurations, one for the ASA ('backend-asa.yaml') and one for StorageGRID ('backend-sgrid.yaml').
F. Create two distinct StorageClasses, 'gold-tier' and 'bronze-tier'.

Answer: A,B,E,F

NEW QUESTION # 39
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