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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

1. Which of the following techniques are used to maximize GPU utilization in AI workloads? (Choose two)

A) Using larger batch sizes
B) Utilizing CPU-based workloads for all tasks
C) Scheduling GPU-intensive tasks during off-peak hours
D) Balancing compute and storage workloads efficiently

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

3. Which AI technology is used to generate new, never-before-seen content such as images or text?

A) Reinforcement AI
B) Generative AI
C) Supervised AI
D) Predictive AI

4. A research lab uses a fleet of autonomous drones to collect high-resolution aerial imagery for agricultural analysis. The drones land at a remote edge location and offload their data. The AI models for image analysis are trained at a central data center. The team is using NetApp SnapMirror to replicate the data from the edge to the core. However, the data scientists are complaining that the datasets arriving at the data center are often incomplete or corrupted.
An administrator reviews the SnapMirror configuration and status via the BlueXP API:
{
"source": { "workingEnvironmentId": "OnPrem-Edge-Filer-1", "volumeName": "drone_data_raw" },
"destination": { "workingEnvironmentId": "Core-Datacenter-A800", "volumeName":
"drone_data_replicated" },
"mirrorState": "broken-off",
"relationshipStatus": "idle",
"unhealthyReason": "Transfer failed. Destination volume is out of space.", "lastTransferInfo": {
"transferError": "No space left on device"
}
}
What is the direct cause of the incomplete datasets at the data center?

A) The source volume at the edge location has become corrupted.
B) The BlueXP Connector does not have the correct permissions to manage the SnapMirror relationship.
C) The SnapMirror relationship is broken because the destination volume at the core data center has run out of capacity.
D) The network connection between the edge and the core is unreliable.

5. A media company is building a new generative AI service. The project has two main components:
1. Data Lake & Fine-Tuning: A 300 TB repository of unstructured data (videos, images, text) stored as objects will be used to fine-tune a foundational model. This process requires a scalable, cost-effective storage solution that can integrate with cloud-native data processing tools like Apache Spark.
2. Inference & RAG: The fine-tuned model will be used in a customer-facing application that leverages Retrieval-Augmented Generation (RAG). To ensure low-latency responses, the RAG component requires extremely fast lookups from a 10 TB vector database.
The company needs a solution that optimizes both cost and performance for this entire lifecycle.
Which combination of NetApp technologies provides the most appropriate solution for this scenario?

A) Use NetApp StorageGRID for the data lake and a NetApp ASA system for the vector database.
B) Use a single, large NetApp ASA system for both the object data lake and the vector database.
C) Use NetApp Cloud Volumes ONTAP for the data lake and NetApp StorageGRID for the vector database.
D) Use NetApp E-Series for the data lake and a NetApp ASA system for the vector database.

Solutions: