Network Appliance NS0-901 valid exam dumps : NetApp Certified AI Expert Exam

  • Exam Code: NS0-901
  • Exam Name: NetApp Certified AI Expert Exam
  • Updated: Aug 21, 2026
  • Q&As: 106 Questions and Answers

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Network Appliance NS0-901 Exam Syllabus Topics:

SectionWeightObjectives
AI Overview15%- AI Convergence with HPC and Analytics
  • 1. Leveraging shared infrastructure for AI, HPC, and analytics
- AI Industry Applications
  • 1. Agents
  • 2. Healthcare applications
  • 3. Digital twins
- AI Deployment Models
  • 1. Edge
  • 2. Cloud
  • 3. Benefits and risks of each model
  • 4. On-premises
- Machine Learning Fundamentals
  • 1. Describe machine learning benefits
  • 2. Understand the relationship between AI, machine learning, and deep learning
- Training vs. Inferencing vs. Predictions
  • 1. Distinguish between training and inference workloads
- Algorithm Types
  • 1. Unsupervised learning
  • 2. Supervised learning
  • 3. Reinforcement learning
AI Lifecycle27%- Model Development
  • 1. Fine-tuning workflows
  • 2. Model building
  • 3. Inferencing
- Data Preparation
  • 1. XCP and CopySync
  • 2. NetApp BlueXP Classification
  • 3. Data aggregation and cleansing
- Generative AI Concepts
  • 1. Hallucinations
  • 2. Fine-tuning
  • 3. Retrieval Augmented Generation (RAG)
- 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
AI Common Challenges22%- 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. Sizing storage and compute resources effectively
  • 2. Controlling costs and securing storage
AI Hardware Architectures18%- NetApp Architectures
  • 1. OVX architectures
  • 2. BasePod
  • 3. SuperPOD
- Networking and Storage
  • 1. Network protocols for AI workloads
  • 2. Storage architectures for AI
- Infrastructure Topologies
  • 1. Data aggregation and compute topologies
AI Software Architectures18%- 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
- Scaling and Orchestration
  • 1. Leveraging BlueXP software tools
  • 2. Scaling AI workloads with Kubernetes

Network Appliance NetApp Certified AI Expert Sample Questions:

1. An AI architect is designing a storage solution for a new training cluster. The primary workload consists of training large language models, which involves sequential reads of massive datasets.
The key requirement is to maximize GPU utilization by providing the highest possible data throughput. Cost is a secondary concern to performance.
Which NetApp storage system is the most appropriate choice for this workload?

A) NetApp ASA (All-SAN Array)
B) NetApp C-Series
C) NetApp E-Series
D) NetApp StorageGRID


2. The HPC cluster generates simulation data at an extremely high rate, requiring a storage system that can handle massively parallel writes from hundreds of compute nodes simultaneously. Which storage system and file protocol combination is the most appropriate choice for the HPC cluster's high-performance scratch space?

A) A NetApp ASA system serving a single, large NFS volume.
B) A NetApp StorageGRID system accessed via the S3 protocol.
C) A Cloud Volumes ONTAP instance with a standard file system.
D) A NetApp E-Series system serving a BeeGFS parallel file system.


3. Given the company's goal of combining physics-based simulations with AI-driven analytics on a shared data foundation, which industry trend does this project best represent?

A) The exclusive use of public cloud resources for all computational tasks.
B) The separation of AI and HPC into dedicated, air-gapped environments.
C) The convergence of AI, High-Performance Computing (HPC), and analytics on a unified data infrastructure.
D) The replacement of all physical testing with digital simulations.


4. A security administrator is reviewing the configuration of a production ONTAP cluster after a compliance audit. The audit requires that all volumes containing financial data must be protected against ransomware. The administrator runs a command to check the status of Autonomous Ransomware Protection (ARP) on a critical volume.
The command and its output are as follows:
cluster-1::> security ransomware anti-ransomware show -vserver svm_finance -volume finance_q1_data Vserver: svm_finance Volume: finance_q1_data Autonomous Ransomware Protection Status: disabled Learning Mode: normal Dry Run Mode: false Action on Detection: notify Based on this output, what is the primary security risk for the 'finance_q1_data' volume?

A) The action on detection is set only to "notify," which will not block the attack.
B) The learning mode is set to "normal," which may not detect zero-day attacks.
C) The volume is vulnerable to ransomware because Autonomous Ransomware Protection is not enabled.
D) The volume is not part of any Snapshot schedule.


5. A financial services company has deployed a real-time fraud detection model at the edge. The model is designed for low-latency inference. However, monitoring reports indicate that the infrastructure costs are excessively high, and GPU utilization is consistently low. The architect reviews the deployment configuration.
Instance_Type: NVIDIA DGX A100 (8 GPUs)
Storage_Tier: High-Performance All-Flash (NetApp ASA)
Network: 100GbE RoCE
GPU_Utilization_Avg: 5%
Monthly_Cost: $15,000
Workload_Profile: Low-volume, sporadic, real-time predictions
What is the most likely cause of the high costs and low utilization?

A) The model was trained using supervised learning, which is inefficient for fraud detection.
B) The network latency is too high for an edge deployment.
C) The compute and storage infrastructure is sized for a large-scale training workload, not a lightweight inference workload.
D) The storage tier is too slow, causing the GPUs to wait for data.


Solutions:

Question # 1
Answer: A
Question # 2
Answer: D
Question # 3
Answer: C
Question # 4
Answer: C
Question # 5
Answer: C

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