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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Weight	Objectives
AI Lifecycle	27%	- Model Development 1. Inferencing 2. Model building 3. Fine-tuning workflows - Data Preparation 1. Data aggregation and cleansing 2. NetApp BlueXP Classification 3. XCP and CopySync - Generative AI Concepts 1. Retrieval Augmented Generation (RAG) 2. Fine-tuning 3. Hallucinations - Predictive AI vs. Generative AI 1. Impact of generative content (text, images, video, decision-making) 2. Distinction between predictive and generative AI 3. Large Language Models (LLMs)
AI Overview	15%	- AI Deployment Models 1. Benefits and risks of each model 2. Cloud 3. Edge 4. On-premises - Machine Learning Fundamentals 1. Describe machine learning benefits 2. Understand the relationship between AI, machine learning, and deep learning - AI Convergence with HPC and Analytics 1. Leveraging shared infrastructure for AI, HPC, and analytics - Training vs. Inferencing vs. Predictions 1. Distinguish between training and inference workloads - Algorithm Types 1. Unsupervised learning 2. Reinforcement learning 3. Supervised learning - AI Industry Applications 1. Agents 2. Digital twins 3. Healthcare applications
AI Common Challenges	22%	- Resource Management 1. Controlling costs and securing storage 2. Sizing storage and compute resources effectively - Traceability and Optimization 1. Maximizing performance in demanding AI workloads 2. Optimizing data access and movement 3. Ensuring traceability for code, data, and models
AI Hardware Architectures	18%	- Infrastructure Topologies 1. Data aggregation and compute topologies - NetApp Architectures 1. OVX architectures 2. SuperPOD 3. BasePod - Networking and Storage 1. Storage architectures for AI 2. Network protocols for AI workloads
AI Software Architectures	18%	- Scaling and Orchestration 1. Leveraging BlueXP software tools 2. Scaling AI workloads with Kubernetes - MLOps and LLMOps Ecosystems 1. Understanding the software tools and platforms enabling AI at scale - Development Tools 1. NetApp DataOps Toolkit 2. Jupyter notebooks vs. pipelines

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q21-Q26):

NEW QUESTION # 21
What is the primary role of NetApp Trident in a Kubernetes environment designed for AI workloads?

A. To act as a dynamic storage orchestrator, provisioning persistent storage from NetApp backends on- demand for containerized applications.
B. To provide a web-based IDE, like Jupyter, for data scientists to develop models.
C. To directly accelerate GPU computations using specialized drivers.
D. To function as a container runtime interface for executing AI models.

Answer: A

NEW QUESTION # 22
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. Unsupervised learning, which clusters the documents into topics for the model to browse.
D. Retrieval-Augmented Generation (RAG), which fetches relevant information from the documents at query time to inform the model's response.

Answer: D

NEW QUESTION # 23
A junior administrator is attempting to delete an old, unused Snapshot copy from a production volume to reclaim space but receives an error. The administrator is certain they are using the correct command and have the appropriate 'vsadmin' role.
The command and error are shown below:
cluster-1::> volume snapshot delete -vserver svm_prod -volume app_data -snapshot nightly.2025- 06-15_0015 Error: command failed: This operation is not permitted. Deletion of Snapshot copy "nightly.2025-
06-15_0015" on volume "app_data" in Vserver "svm_prod" requires approval.
Use the "security multi-admin-verify approval show" command to view pending approvals.
What is the most likely reason the administrator cannot delete the Snapshot?

A. The volume is protected by SnapLock, and the Snapshot has not reached its expiry date.
B. The Snapshot is locked by a SnapMirror relationship.
C. Multi-Admin Verification (MAV) is enabled, and the destructive operation requires approval from another designated administrator.
D. The 'vsadmin' role does not have permission to delete Snapshots.

Answer: C

NEW QUESTION # 24
A data scientist is using the NetApp DataOps Toolkit for Python to automate the creation of a new, writable volume for an experiment. The script is intended to clone an existing dataset volume. When the script is executed, it fails with an error.
The relevant portion of the Python script is:
from netapp_dataops.k8s import clone_pvc
clone_pvc(
source_pvc_name="dataset-v1-pvc",
new_pvc_name="experiment-clone-pvc",
namespace="ds-team-1"
)
The script produces the following error in the terminal:
'Error: Failed to clone PVC. Source PVC 'dataset-v1-pvc' not found in namespace 'ds-team-1'.' What is the most likely cause of this error?

A. The source PersistentVolumeClaim (PVC) named 'dataset-v1-pvc' does not exist or is in a different namespace.
B. The NetApp DataOps Toolkit does not support cloning volumes.
C. The Python script is missing the necessary import statement for the toolkit.
D. The Kubernetes cluster does not have NetApp Trident installed.

Answer: A

NEW QUESTION # 25
The data science team in Azure reports that training jobs are taking longer than expected. An analysis of the Cloud Volumes ONTAP instance in Azure shows that the instance type is undersized for the I/O demands of the training workload. The architect needs to change the Azure VM instance type for the Cloud Volumes ONTAP system to a more powerful one.
The current configuration is:
Cloud_Provider: Azure
ONTAP_System: Cloud Volumes ONTAP (Single Node)
Current_Instance_Type: Standard_DS3_v2
Target_Instance_Type: Standard_E8s_v4
What is the most direct method to perform this operation using NetApp's management tools?

A. Terminate the existing Cloud Volumes ONTAP instance and deploy a new one with the target instance type, then restore data from backup.
B. SSH to the Cloud Volumes ONTAP instance and run an ONTAP command to modify the underlying VM.
C. Use the Azure portal to manually change the VM instance type.
D. From the BlueXP Canvas, select the Cloud Volumes ONTAP working environment and use the
"Change Instance Type" action in the Features panel.

Answer: D

NEW QUESTION # 26
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