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Network Appliance NS0-901 Exam Syllabus Topics:

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

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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q84-Q89):

NEW QUESTION # 84
Which of the following are typical requirements for inferencing in AI models? (Choose two)

A. Cloud-based inference only
B. Extensive training data
C. Loading the model into memory
D. Pre-trained models

Answer: C,D

NEW QUESTION # 85
The firm's CFO is concerned about the rising costs of the on-premises AI infrastructure. A storage utilization report shows that of the 200 TB of data on the high-performance AFF A-Series, 150 TB consists of inactive, older versions of product documents that are rarely accessed but must be kept online for regulatory reasons.
The current storage landscape is:
- Performance Tier: NetApp AFF A-Series (200 TB used)
- Capacity Tier: NetApp StorageGRID (1.5 PB used)
What is the most effective and automated solution to reduce the storage cost of the performance tier without impacting data accessibility?

A. Use NetApp SnapMirror to replicate the entire 200 TB volume to the StorageGRID system and then delete the source.
B. Manually identify and delete the 150 TB of inactive data from the AFF A-Series.
C. Purchase an additional, larger AFF A-Series system to gain better storage efficiency through deduplication.
D. Implement NetApp FabricPool to automatically tier the inactive data blocks from the AFF A-Series to the StorageGRID system.

Answer: D

NEW QUESTION # 86
A team has deployed a Retrieval-Augmented Generation (RAG) system to answer customer queries. Recently, users have complained that the answers provided by the chatbot are outdated and do not reflect the latest product updates. An architect investigates and finds the following status log from the RAG pipeline's data ingestion monitor.
Timestamp: 2025-07-11T14:00:00Z
System: RAG Pipeline Monitor
Status: WARNING
Message: Vector DB freshness check failed.
Source data appears stale.
Vector_DB_Last_Update: 2025-06-10T08:00:00Z
Knowledge_Base_Last_Modified: 2025-07-11T13:15:00Z
Data_Sync_Service: BlueXP copy and sync
Sync_Job_Status: Succeeded
Based on the log, what is the most likely cause of the outdated answers?

A. The knowledge base itself has not been updated with the latest product information.
B. The process that converts staged documents into vectors and updates the vector database is not running.
C. The BlueXP copy and sync service is failing to copy data to the staging area.
D. The LLM needs to be fine-tuned with the new product information.

Answer: B

NEW QUESTION # 87
A data scientist needs to launch a Jupyter notebook as a pod in a Kubernetes cluster. The pod requires a 50 Gi persistent volume for storing datasets and notebooks. The cluster administrator has configured a default Trident StorageClass for general-purpose use. The data scientist has the following PersistentVolumeClaim (PVC) manifest:
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: jupyter-pvc
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 50Gi
When this PVC is applied to the cluster, what will be the result?

A. The PVC will remain in a "Pending" state until a PersistentVolume is manually created.
B. Trident will create a 1 Gi volume, as this is the default size for all PVCs.
C. Trident will automatically provision a 50 Gi volume on its default backend and bind it to the PVC.
D. The PVC will fail because a 'storageClassName' is not explicitly defined.

Answer: C

NEW QUESTION # 88
The company's finance department mandates a cost-control strategy for the petabyte-scale StorageGRID data lake. The analysis shows that 80% of the simulation data is not accessed after
90 days but must be retained for five years for regulatory compliance. Which StorageGRID feature should the architect use to automatically reduce the long-term storage costs for this inactive data?

A. Implement a FabricPool policy to tier the data to a NetApp ASA system.
B. Enable deduplication and compression on all StorageGRID storage nodes.
C. Use NetApp SnapMirror to replicate the cold data to a different, lower-cost StorageGRID cluster.
D. Configure an Information Lifecycle Management (ILM) policy that automatically moves objects older than 90 days to a lower-cost cloud archive tier, such as Amazon S3 Glacier Deep Archive.

Answer: D

NEW QUESTION # 89
......

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