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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

1. The company decides to establish a disaster recovery (DR) site in a secondary data center for the entire Digital Twin platform. The DR plan must protect the HPC data, the AI training data, and the central data lake.
The DR requirements are:
- RPO: 4 hours for all data.
- RTO: 24 hours for the entire platform.
- Process: The failover and failback process should be as automated as possible.
Which combination of technologies provides the most comprehensive DR solution?

A) Use NetApp SnapMirror for the ASA, StorageGRID's built-in replication for the data lake, and a host- based tool like 'rsync' for the E-Series/BeeGFS data, all orchestrated via BlueXP disaster recovery.
B) Use BlueXP backup and recovery to back up all three storage systems (ASA, E-Series, StorageGRID) to a single cloud target.
C) Use NetApp SnapMirror for the ASA, StorageGRID replication for the data lake, and rely on tape backups for the E-Series/BeeGFS data.
D) Deploy a MetroCluster configuration spanning the primary and DR sites for all three storage systems.

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

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

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

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

4. A development team is building a generative AI application that must answer questions based on a constantly changing internal knowledge base of company documents. They want to provide the model with up-to-date information without altering its core weights and capabilities.
Which approach is most suitable for this requirement?

A) Predictive AI, which analyzes the documents to forecast future questions.
B) Fine-tuning, which retrains the model's last few layers on the new documents.
C) Retrieval-Augmented Generation (RAG), which fetches relevant information from the documents at query time to inform the model's response.
D) Unsupervised learning, which clusters the documents into topics for the model to browse.

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

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

Solutions: