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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

Question 1

Which storage protocols are commonly used for handling large-scale AI data? (Choose two)

A. File-based systems
B. POSIX-based file systems
C. Object-based storage
D. Parallel file systems

Question 2

The HPC cluster generates simulation data at an extremely high rate, requiring a storage system that can handle massively parallel writes from hundreds of compute nodes simultaneously. Which storage system and file protocol combination is the most appropriate choice for the HPC cluster's high-performance scratch space?

A. A NetApp ASA system serving a single, large NFS volume.
B. A NetApp E-Series system serving a BeeGFS parallel file system.
C. A Cloud Volumes ONTAP instance with a standard file system.
D. A NetApp StorageGRID system accessed via the S3 protocol.

Question 3

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

Question 4

Which of the following platforms can be used to manage containerized AI workloads on Kubernetes? (Choose two)

A. Google VertexAI
B. KubeFlow
C. TensorFlow Extended
D. RunAI

Question 5

An organization is developing a new AI-powered application. The initial phase involves feeding a curated 50 TB dataset of labeled images into a complex neural network, allowing the model to learn and adjust its internal parameters over millions of iterations. The second phase involves deploying this finalized model to a web service where it will process single, user-uploaded images and return a classification in real-time.
Which statement accurately describes these two phases?

A. Phase 1 is inferencing, and Phase 2 is training.
B. Both Phase 1 and Phase 2 are examples of training.
C. Both Phase 1 and Phase 2 are examples of inferencing.
D. Phase 1 is training, and Phase 2 is inferencing.

Solutions: