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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Objectives
AI and Machine Learning Fundamentals	- Algorithm types 1. Reinforcement learning 2. Supervised learning 3. Unsupervised 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. Data governance and management 2. Scalability and performance optimization - End-to-end AI lifecycle 1. Model training and validation 2. Model deployment and monitoring 3. Data ingestion and preparation
Industry Use Cases	- AI applications across industries 1. Autonomous systems and agents 2. Healthcare AI 3. Digital twins
AI Infrastructure and NetApp Solutions	- AI-ready data infrastructure 1. High-performance storage for AI workloads 2. Data pipeline optimization for AI/ML workloads - Converged workloads 1. Shared infrastructure design considerations 2. AI, HPC, and analytics convergence

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q85-Q90):

NEW QUESTION # 85
A company is running its AI training workloads on a NetApp AFF A-Series system. To manage costs, they want to automatically move inactive training datasets and older model checkpoints from the high- performance all-flash tier to a lower-cost object storage tier, such as an on- premises StorageGRID or a public cloud bucket. The process must be transparent to the data scientists and not require changes to their scripts or file paths.
Which two NetApp technologies should be combined to achieve this goal? (Choose 2.)

A. NetApp SnapMirror
B. NetApp XCP
C. NetApp FabricPool
D. NetApp FlexCache
E. NetApp StorageGRID

Answer: C,E

NEW QUESTION # 86
What is the primary difference between C-Series and A-Series storage for AI workloads?

A. C-Series supports both file and object-based storage, while A-Series is optimized for object storage.
B. A-Series is for smaller-scale AI workloads, while C-Series supports large-scale, high-performance AI applications.
C. A-Series provides GPU-based acceleration, while C-Series only supports CPU-based workloads.
D. C-Series is designed for high-performance workloads, while A-Series focuses on cost-efficiency for general storage.

Answer: D

NEW QUESTION # 87
A financial services company has deployed a real-time fraud detection model at the edge. The model is designed for low-latency inference. However, monitoring reports indicate that the infrastructure costs are excessively high, and GPU utilization is consistently low. The architect reviews the deployment configuration.
Instance_Type: NVIDIA DGX A100 (8 GPUs)
Storage_Tier: High-Performance All-Flash (NetApp ASA)
Network: 100GbE RoCE
GPU_Utilization_Avg: 5%
Monthly_Cost: $15,000
Workload_Profile: Low-volume, sporadic, real-time predictions
What is the most likely cause of the high costs and low utilization?

A. The network latency is too high for an edge deployment.
B. The model was trained using supervised learning, which is inefficient for fraud detection.
C. The compute and storage infrastructure is sized for a large-scale training workload, not a lightweight inference workload.
D. The storage tier is too slow, causing the GPUs to wait for data.

Answer: C

NEW QUESTION # 88
The AI training jobs on the AIPod are performing below expectations. The NVIDIA DGX servers' GPUs show low utilization. A performance analysis reveals that the bottleneck is not the storage system itself, but the network path between the storage and the compute nodes.
The current network configuration is as follows:
Network_Fabric: 100GbE Standard Ethernet
Protocol: NFS over TCP/IP
Data_Path: Storage -> Host CPU -> GPU Memory
Which network architecture enhancement would provide the most significant performance improvement by reducing latency and CPU overhead?

A. Add more 100GbE network ports to the storage controllers.
B. Isolate the storage traffic on a separate VLAN from the management traffic.
C. Implement RDMA over Converged Ethernet (RoCE) and configure GPUDirect Storage.
D. Upgrade the network switches to a model with a larger packet buffer.

Answer: C

NEW QUESTION # 89
The firm decides to implement a disaster recovery (DR) site for the "Advisor Assistant" application in a secondary data center. The Recovery Point Objective (RPO) is 15 minutes, and the Recovery Time Objective (RTO) is 4 hours. The design must protect both the document data lake and the vector database.
The primary site contains:
- Data Lake: NetApp StorageGRID
- Vector DB: NetApp AFF A-Series
Which combination of technologies and processes provides a complete and robust DR solution?
(Select all that apply.)

A. Use NetApp SnapMirror to create an asynchronous replication relationship for the AFF A-Series volume containing the vector database, with a schedule of 10 minutes.
B. Use NetApp FlexCache at the DR site to cache data from the primary site.
C. Use BlueXP disaster recovery to orchestrate and automate the failover and failback workflows for the application and its data dependencies.
D. Use the NetApp DataOps Toolkit to manually script the failover process.
E. Use StorageGRID's built-in replication rules to replicate object data from the primary site's grid to a StorageGRID instance at the DR site.
F. Rely on tape backups to be shipped to the DR site in the event of a disaster.

Answer: A,C,E

NEW QUESTION # 90
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