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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

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

2. Which of the following describes the impact of generative AI in content creation?

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

3. An organization is planning to deploy a large AI infrastructure but wants to avoid a large, upfront capital expenditure. They prefer an operational expenditure (OpEx) model where they pay for storage and compute resources as they are consumed. They also need the flexibility to scale resources up or down based on project demands.
Which NetApp consumption model is specifically designed to meet these financial and operational requirements?

A) A standard capital purchase of AFF and ASA systems.
B) NetApp Keystone, which provides a subscription-based, pay-as-you-go service for on-premises and cloud storage.
C) A perpetual licensing model for all ONTAP software features.
D) NetApp Cloud Volumes ONTAP PAYGO licensing only.

4. An AI platform is suffering from poor performance during distributed training jobs. The training data resides on a single, large NFS volume. Monitoring shows that while the overall network throughput to the storage system is high, individual GPU nodes experience significant I/O wait times, and the single ONTAP volume is becoming a performance bottleneck. The goal is to re- architect the storage layout to maximize read parallelism and throughput for the training cluster.
Which two actions should the architect take to address this performance bottleneck? (Choose 2.)

A) Implement a NetApp FlexGroup volume to spread the dataset across multiple constituent volumes and aggregates.
B) Replace the NFS protocol with iSCSI for all training data access.
C) Enable QoS maximums on the training volume to limit its IOPS.
D) Increase the number of network ports connected to the storage controller.
E) Use NetApp FlexCache to create a local cache of the training data on each compute node.

5. What is the primary role of NetApp Trident in a Kubernetes environment designed for AI workloads?

A) To provide a web-based IDE, like Jupyter, for data scientists to develop models.
B) To act as a dynamic storage orchestrator, provisioning persistent storage from NetApp backends on- demand for containerized applications.
C) To function as a container runtime interface for executing AI models.
D) To directly accelerate GPU computations using specialized drivers.

Solutions: