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Network Appliance NS0-901 Exam Syllabus Topics:

Network Appliance NetApp Certified AI Expert Sample Questions:

Question 1

In the data pipeline, which NetApp technology is used to create an efficient, block-level, incremental replication of the anonymized datasets from the on-premises ASA to the Cloud Volumes ONTAP instance in Azure?

A. NetApp SnapMirror
B. NetApp FabricPool
C. NetApp XCP
D. NetApp BlueXP copy and sync

Question 2

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

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

Question 3

An AI research team is experiencing slow model training times. Their performance monitoring indicates that the GPUs are frequently idle, waiting for data. They want to implement a single technology change to create a more direct data path between their storage and GPUs.
Their current setup is as follows:
Compute: Server with NVIDIA A100 GPUs
Storage: NetApp AFF A-Series (All-Flash)
Network: 100GbE Ethernet
Data_Path: Storage -> Host CPU/Memory -> GPU Memory
Which technology should the architect recommend to specifically address this data path inefficiency?

A. NetApp SnapMirror
B. NetApp FabricPool
C. A faster CPU in the server
D. GPUDirect Storage

Question 4

A robotics company is developing a control system for an autonomous warehouse drone. The drone must learn to navigate complex environments to pick up packages. The development team has created a physics-based simulation where the drone can attempt the task millions of times.
The drone receives a positive reward for successfully retrieving a package and a negative penalty for collisions. Which type of machine learning algorithm is being used in this scenario?

A. Generative learning
B. Supervised learning
C. Reinforcement learning
D. Unsupervised learning

Question 5

An AI infrastructure architect is tasked with designing a solution to address two critical challenges in a large, multi-petabyte AI environment:
1. Cost: A significant portion of the data on the high-performance all-flash storage is inactive but must remain online. The cost of storing this cold data on the performance tier is prohibitive.
2. Traceability: Data scientists need a simple, space-efficient way to version their datasets at key points in their workflow to ensure reproducibility.
The environment consists of NetApp AFF A-Series and NetApp StorageGRID systems.
Which combination of NetApp technologies should the architect implement to solve both challenges simultaneously? (Select all that apply.)

A. Use NetApp XCP to periodically move cold data from the AFF systems to StorageGRID.
B. Implement NetApp FlexClone to create full, writable copies of datasets for each experiment.
C. Train data scientists to use NetApp Snapshots to create point-in-time, read-only versions of their data volumes.
D. Use BlueXP backup and recovery to create backups on StorageGRID, then delete the original volumes from the AFF systems.
E. Use NetApp SnapMirror to replicate volumes from the AFF systems to StorageGRID for archival.
F. Implement NetApp FabricPool to automatically tier cold data blocks from the AFF systems to StorageGRID.

Solutions: