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Updated: Aug 13, 2026
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| Certification Vendor: | NetApp (Network Appliance) |
| Exam Name: | NetApp Certified AI Expert Exam |
| Exam Number: | NS0-901 |
| Exam Duration: | 90 minutes |
| Available Languages: | English |
| Real Exam Qty: | 60 |
| Exam Format: | Multiple-choice, Scenario-based questions |
| Exam Price: | 250 USD |
| Certificate Validity Period: | 2 years |
| Passing Score: | 66% |
| Recommended Training: | NetApp Learning Services - AI Expert Training |
| Exam Registration: | Pearson VUE Registration |
| Sample Questions: | Network Appliance NS0-901 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | 6–12 months of technical experience with AI workloads; knowledge of NetApp ONTAP, AI frameworks, and data workflows |
| Official Syllabus URL: | https://www.netapp.com/support-and-training/netapp-learning-services/certifications/ai-expert/ |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Overview | 15% | - Algorithm types: supervised, unsupervised, reinforcement learning - AI deployment models: on-premises, cloud, edge - AI industry use cases and applications - AI, machine learning, and deep learning concepts - Convergence of AI, high-performance computing, and analytics |
| Topic 2: AI Lifecycle | 27% | - AI lifecycle stages: design, training, deployment, monitoring - Model training, inference, and optimization - Predictive vs generative AI - Data preparation and management for AI - AI governance, ethics, and compliance |
| Topic 3: NetApp AI Solutions and Architecture | 25% | - Storage architectures for AI workloads - ONTAP integration with AI frameworks - Data management and data pipeline design - Scalability and performance optimization for AI - NetApp AI-ready infrastructure components |
| Topic 4: Cloud and Hybrid Cloud AI Deployment | 18% | - Data mobility and consistency across environments - Cloud-native AI solutions and integration - NetApp cloud data services for AI - Hybrid and multi-cloud AI architectures |
| Topic 5: Security, Reliability, and Operations | 15% | - Data security and access control for AI - Monitoring, logging, and troubleshooting AI environments - High availability and data protection - Cost management and efficiency |
1. The Chief Information Security Officer (CISO) is concerned about the risk of a ransomware attack encrypting the critical vector database hosted on the NetApp AFF A-Series. The CISO wants a solution that can proactively detect and block a live attack in real-time, not just recover from a backup after the fact.
Which NetApp security feature should the architect enable on the vector database volume to meet this requirement?
A) NetApp Volume Encryption (NVE)
B) NetApp SnapLock (Compliance Mode)
C) Autonomous Ransomware Protection (ARP)
D) Multi-Admin Verification (MAV)
2. 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.
3. 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) NetApp SnapLock to make the source data immutable before scanning.
C) A manual review process where technicians visually inspect each scan for PII.
D) NetApp BlueXP classification, configured to scan the on-premises ASA working environment.
E) A custom "PII" category within BlueXP classification to identify specific medical record number formats.
4. The firm wants to extend the "Advisor Assistant" to include a new batch processing feature. Every night, the system must analyze every client portfolio against a set of 50 different risk models and generate a compliance report. This is a highly parallel, read-intensive workload. The architect must design a data workflow that is efficient and does not impact the production chatbot environment. Which sequence of actions and technologies provides the most effective solution?
A) Create a full physical copy of the client portfolio database to a separate volume, mount it to the compute nodes, and run the analysis.
B) Create a NetApp Snapshot of the portfolio database volume, create a FlexClone from that snapshot, mount the FlexClone to the analysis pods, and run the batch job.
C) Run the analysis job directly against the production portfolio database during off-peak hours.
D) Use NetApp SnapMirror to replicate the portfolio database volume to the DR site, and run the analysis jobs there.
5. 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 C-Series
B) NetApp ASA (All-SAN Array)
C) NetApp E-Series
D) NetApp StorageGRID
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: D,E | Question # 4 Answer: B | Question # 5 Answer: B |
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