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Network Appliance NS0-901 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Overview | 15% | - Training vs. Inferencing vs. Predictions
|
| Topic 2: AI Hardware Architectures | 18% | - NetApp Architectures
|
| Topic 3: AI Lifecycle | 27% | - Model Development
|
| Topic 4: AI Common Challenges | 22% | - Resource Management
|
| Topic 5: AI Software Architectures | 18% | - Development Tools
|
Network Appliance NetApp Certified AI Expert Sample Questions:
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. Reinforcement learning
- B. Generative learning
- C. Unsupervised learning
- D. Supervised learning
Correct Answer: A 🗳️
To meet HIPAA compliance, the first step in the data pipeline is to identify all medical scans that contain embedded PII. The solution must be automated and capable of scanning data in-place on the on-premises ASA system.
Which two technologies should be used to accomplish this identification and tagging task?
(Choose 2.)
- A. A custom Python script that uses regular expressions to search file contents.
- B. A manual review process where technicians visually inspect each scan for PII.
- C. NetApp SnapLock to make the source data immutable before scanning.
- D. A custom "PII" category within BlueXP classification to identify specific medical record number formats.
- E. NetApp BlueXP classification, configured to scan the on-premises ASA working environment.
Correct Answer: D,E 🗳️
An MLOps engineer is troubleshooting a failed Kubeflow pipeline step. The step was designed to create a clone of a dataset for a training job using the NetApp DataOps Toolkit. The pod logs for the failed pipeline step show the following:
Traceback (most recent call last):
File "create_clone.py", line 15, in <module>
clone_pvc(source_pvc_name="training-data-v2", new_pvc_name="train-job-34a-data") NameError: name 'clone_pvc' is not defined The engineer reviews the Python script for the pipeline step:
# create_clone.py
import os
from netapp_dataops.k8s import create_pvc
# Other code
print("Cloning source dataset for training run...")
clone_pvc(
source_pvc_name="training-data-v2",
new_pvc_name="train-job-34a-data"
)
print("Clone created successfully.")
What is the cause of the error?
- A. The Python script is attempting to use the 'clone_pvc' function, but it was not imported from the
'netapp_dataops.k8s' library. - B. The Kubernetes cluster is not running NetApp Trident.
- C. The source PVC 'training-data-v2' does not exist.
- D. The NetApp DataOps Toolkit is not installed in the container image used for this pipeline step.
Correct Answer: A 🗳️
An architect is designing a cost-optimized storage solution for a large AI environment that has two distinct data temperature profiles:
1. Hot Data (200 TB): Actively used training sets and models requiring all-flash performance.
2. Cold Data (2 PB): Inactive, archived datasets and old model versions that must remain online but are infrequently accessed.
The solution must automatically manage data placement based on activity, without requiring manual intervention or changes to file paths. The environment consists of an on-premises data center and a public cloud account.
Which combination of NetApp technologies provides the most complete and cost-effective solution? (Select all that apply.)
- A. Deploy a single, large Cloud Volumes ONTAP instance to hold both the hot and cold data tiers.
- B. Use NetApp XCP to manually script the daily movement of cold files from the AFF system to StorageGRID.
- C. Deploy NetApp StorageGRID on-premises to serve as a cost-effective capacity tier for the cold data.
- D. Deploy a NetApp AFF A-Series system on-premises to serve as the high-performance tier for the hot data.
- E. Use NetApp SnapMirror to create a full copy of the 2 PB of cold data on the AFF A-Series for faster access if needed.
- F. Use NetApp FabricPool to automatically and transparently tier cold data blocks from the AFF A- Series to the StorageGRID system.
Correct Answer: C,D,F 🗳️
The firm has acquired a competitor, and the volume of proprietary documents for the "Advisor Assistant" is expected to triple, exceeding the capacity of the current StorageGRID data lake. The architect needs to expand the data lake's capacity non-disruptively.
The current StorageGRID status is:
System_Health: Nominal
Node_Count: 6 (3 Storage Nodes, 3 Admin/Gateway Nodes)
Usable_Capacity: 1.5 PB
Used_Capacity: 1.4 PB (93%)
What is the standard procedure for scaling the capacity of the on-premises NetApp StorageGRID system?
- A. Replace the disks in the existing storage nodes with higher-capacity drives.
- B. Add new storage nodes to the existing StorageGRID system and execute an expansion procedure.
- C. Provision a new, separate StorageGRID system and use BlueXP copy and sync to move the data.
- D. Use FabricPool to tier the excess data from StorageGRID to a public cloud provider.
Correct Answer: B 🗳️
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