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Network Appliance NS0-901 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI Hardware Architectures	18%	- NetApp Architectures 1. OVX architectures 2. SuperPOD 3. BasePod - Infrastructure Topologies 1. Data aggregation and compute topologies - Networking and Storage 1. Network protocols for AI workloads 2. Storage architectures for AI
Topic 2: AI Common Challenges	22%	- Traceability and Optimization 1. Ensuring traceability for code, data, and models 2. Optimizing data access and movement 3. Maximizing performance in demanding AI workloads - Resource Management 1. Controlling costs and securing storage 2. Sizing storage and compute resources effectively
Topic 3: AI Overview	15%	- Training vs. Inferencing vs. Predictions 1. Distinguish between training and inference workloads - Machine Learning Fundamentals 1. Describe machine learning benefits 2. Understand the relationship between AI, machine learning, and deep learning - Algorithm Types 1. Unsupervised learning 2. Reinforcement learning 3. Supervised learning - AI Deployment Models 1. Cloud 2. Benefits and risks of each model 3. Edge 4. On-premises - AI Industry Applications 1. Digital twins 2. Healthcare applications 3. Agents - AI Convergence with HPC and Analytics 1. Leveraging shared infrastructure for AI, HPC, and analytics
Topic 4: AI Lifecycle	27%	- Model Development 1. Inferencing 2. Fine-tuning workflows 3. Model building - Generative AI Concepts 1. Fine-tuning 2. Hallucinations 3. Retrieval Augmented Generation (RAG) - Data Preparation 1. XCP and CopySync 2. NetApp BlueXP Classification 3. Data aggregation and cleansing - Predictive AI vs. Generative AI 1. Large Language Models (LLMs) 2. Impact of generative content (text, images, video, decision-making) 3. Distinction between predictive and generative AI
Topic 5: AI Software Architectures	18%	- Scaling and Orchestration 1. Scaling AI workloads with Kubernetes 2. Leveraging BlueXP software tools - Development Tools 1. NetApp DataOps Toolkit 2. Jupyter notebooks vs. pipelines - MLOps and LLMOps Ecosystems 1. Understanding the software tools and platforms enabling AI at scale

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q95-Q100):

NEW QUESTION # 95
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 'vsadmin' role does not have permission to delete Snapshots.
B. Multi-Admin Verification (MAV) is enabled, and the destructive operation requires approval from another designated administrator.
C. The Snapshot is locked by a SnapMirror relationship.
D. The volume is protected by SnapLock, and the Snapshot has not reached its expiry date.

Answer: B

NEW QUESTION # 96
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

Answer: C,D

NEW QUESTION # 97
An MLOps engineer is deploying a training pod that requires a high-performance volume. After applying the pod and PVC manifests, the pod remains in a 'Pending' state. The engineer runs
'kubectl describe pod training-pod-7d8c' and sees the following event:
Events:
Type Reason Age From Message
- - - -
Warning FailedScheduling 2m15s
default-scheduler 0/4 nodes are available: 1 node(s) had volume node affinity conflict, 3 node(s) didn't find available persistent volume to bind.
The engineer then inspects the associated PVC and sees its status is also 'Pending'.
What is the most likely cause of this issue?

A. The Trident controller pod has crashed and needs to be restarted.
B. The 'storageClassName' specified in the PVC does not match any existing StorageClass managed by Trident.
C. The Kubernetes scheduler is malfunctioning and cannot assign pods to nodes.
D. The ONTAP backend is out of available capacity to provision a new volume.

Answer: B

NEW QUESTION # 98
Due to the success of the "Advisor Assistant," the number of concurrent users is expected to double in the next quarter. The existing Kubernetes cluster is running at 80% of its GPU capacity during peak hours. The architect must propose a plan to scale the compute infrastructure to handle the increased load.
Which two strategies represent the most effective and scalable solutions? (Choose 2.)

A. Vertically scale the existing nodes by adding more RAM and CPU cores to each one.
B. Horizontally scale the cluster by adding new GPU-equipped nodes.
C. Manually deploy all new application replicas to a single, new, very large "super-node".
D. Configure the Kubernetes Cluster Autoscaler to automatically add new nodes to the cluster from a predefined node pool when GPU demand exceeds current capacity.
E. Replace all existing GPUs with the next-generation model to increase the performance of each node.

Answer: B,D

NEW QUESTION # 99
An AI operations team is troubleshooting why their RAG-based chatbot is providing outdated information. They have confirmed that the vector database embedding process is functioning correctly, but suspect an issue with the initial data synchronization that moves the knowledge base from an on- premises ONTAP file share to a cloud staging bucket.
They inspect the relevant BlueXP copy and sync job and find the following details:
Service: BlueXP copy and sync
Relationship_Name: KB_Sync_to_Vector_Staging
Source: nfs://ontap-cluster-1/vol_kb/docs
Destination: s3://vector-staging-bucket-89a3/latest/
Last_Sync_Status: FAILED
Last_Sync_Time: 2025-07-11T02:00:15Z
Error_Message: "Authentication error:
Unable to access source.
Check export policy on 'vol_kb'."
Based on this information, what is the most direct solution to fix the data pipeline?

A. Check the IAM permissions for the role associated with the S3 bucket.
B. Re-run the vector database embedding job.
C. Modify the NFS export policy on the 'vol_kb' volume on the on-premises ONTAP cluster to grant access to the BlueXP Connector.
D. Fine-tune the LLM with the latest data instead of using the RAG system.

Answer: C

NEW QUESTION # 100
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