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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

1. The firm decides to expand the "Advisor Assistant" project to a new team in a different department. This team needs its own isolated environment. An MLOps engineer attempts to submit a new GPU- intensive job for the new team, but it remains pending. The engineer checks the Run:AI scheduler logs and finds the following entry:
time="2025-07-11T16:45:00Z" level=info msg="Job ds-new-team-job1 cannot be scheduled.
Project 'new-team-project' has exceeded its GPU quota. Quota: 0, Requested: 1, Used: 0." What is the root cause of the scheduling failure?

A) The Run:AI scheduler is offline and cannot process new jobs.
B) The job is requesting a specific type of GPU that is not available in the cluster.
C) A Run:AI project quota has been configured for the new team, but it has been set to zero, effectively blocking them from using any GPU resources.
D) The Kubernetes cluster has no available GPUs.

2. Given the company's goal of combining physics-based simulations with AI-driven analytics on a shared data foundation, which industry trend does this project best represent?

A) The replacement of all physical testing with digital simulations.
B) The convergence of AI, High-Performance Computing (HPC), and analytics on a unified data infrastructure.
C) The exclusive use of public cloud resources for all computational tasks.
D) The separation of AI and HPC into dedicated, air-gapped environments.

3. Which of the following platforms provides tools for model training and deployment specifically for AI workloads?

A) All of the above
B) Google VertexAI
C) RunAI
D) Domino Data Labs

4. An AI platform administrator is trying to deploy a new GenAI toolkit using the BlueXP Workload Factory. The deployment fails, and the administrator examines the API response from BlueXP.
{
"jobId": "we-deploy-genai-987zy",
"status": "FAILED",
"statusCode": 403,
"message":
"Forbidden: The service principal or user account used by the Connector does not have the required permissions on the target subscription to create a new resource group.
Required permission: 'Microsoft.Resources/subscriptions/resourcegroups/write'." } Based on this API response, what is the root cause of the deployment failure?

A) The GenAI toolkit requires a specific license that has not been added to the BlueXP digital wallet.
B) The BlueXP Connector is offline and cannot communicate with the cloud provider.
C) The Azure service principal associated with the BlueXP Connector lacks the necessary IAM role to create resource groups.
D) The selected ONTAP version does not support the GenAI toolkit.

5. An enterprise is planning a generative AI solution to power its internal support chatbot. The architect must choose between a RAG-based approach and fine-tuning a base model. The project stakeholders have provided a list of prioritized requirements.
| Requirement | Priority | Details
|
| | -- | |
| Factual Accuracy | Critical | Must use the latest product documentation, updated daily.
| | Brand Voice & Persona | High | Must respond in the company's specific, formal tone.
| | Development Cost | High | Limited budget for GPU compute hours for model training.
|
| Data Traceability | Critical | Must be able to cite the exact source document for each answer.
|
Which two recommendations should the architect make to best satisfy these requirements?
(Choose 2.)

A) Use RAG exclusively, as prompt engineering alone can fully replicate a specific brand voice and persona.
B) Propose a hybrid approach where a base model is first lightly fine-tuned for persona, then used within a RAG system for factual grounding.
C) Recommend training a new LLM from scratch to ensure both brand voice and factual accuracy are built-in.
D) Prioritize fine-tuning to embed the company's brand voice and persona into the model.
E) Prioritize a RAG architecture to meet the critical requirements for factual accuracy and data traceability.

Solutions: