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Updated: Aug 08, 2026
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| Certification Vendor: | NetApp |
| Exam Name: | NetApp Certified Artificial Intelligence (AI) Expert Exam |
| Exam Number: | NS0-901 |
| Exam Price: | $250 USD |
| Related Certifications: | NetApp Certified Data Administrator (NCDA) NetApp Certified AI Data Infrastructure Expert (combined credential) |
| Real Exam Qty: | 60 |
| Exam Duration: | 90 minutes |
| Passing Score: | 66% |
| Certificate Validity Period: | 24 months (NetApp certification validity policy) |
| Exam Format: | Multiple-choice, Scenario-based questions |
| Available Languages: | English |
| Recommended Training: | NetApp Learning Services |
| Exam Registration: | NetApp Certification Registration (Pearson VUE) NetApp Certification Program Policies |
| Sample Questions: | Network Appliance NS0-901 Sample Questions |
| Exam Way: | Online proctored or Pearson VUE test center |
| Pre Condition: | Recommended: 6–12 months experience in AI infrastructure, data systems, or NetApp ONTAP environments |
| Official Syllabus URL: | https://www.pearsonvue.com/us/en/netapp.html |
| Section | Objectives |
|---|---|
| AI and Machine Learning Fundamentals | - AI, ML, DL concepts
|
| AI Infrastructure and NetApp Solutions | - Converged workloads
|
| Industry Use Cases | - AI applications across industries
|
| AI Lifecycle and Deployment | - End-to-end AI lifecycle
|
1. A data scientist on the team wants to run an experiment on a new vector indexing strategy. To do this, they need a temporary, writable copy of the main vector database. They use the NetApp DataOps Toolkit for Python to automate this process.
The following script is executed:
from netapp_dataops.k8s import clone_pvc
clone_pvc(
source_pvc_name="prod-vector-db-pvc",
new_pvc_name="exp-indexing-clone",
namespace="ds-prod"
)
Assuming the source PVC exists and the user has correct permissions, what is the primary benefit of using this method?
A) It uses NetApp FlexClone technology to create a near-instantaneous, space-efficient writable copy of the volume, accelerating the experimental workflow.
B) It creates a full physical copy of the data, providing the best performance isolation.
C) It automatically migrates the data from the AFF A-Series to the StorageGRID system for the experiment.
D) It creates a read-only Snapshot, ensuring the integrity of the experimental data.
2. 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 directly accelerate GPU computations using specialized drivers.
C) To provide a web-based IDE, like Jupyter, for data scientists to develop models.
D) To function as a container runtime interface for executing AI models.
3. An AI infrastructure team is selecting a storage protocol for a new, high-performance computing (HPC) cluster that will be used for a weather modeling AI application. The application requires extremely high-throughput, parallel access from hundreds of compute nodes to a shared dataset.
The workload characteristics are as follows:
Access_Pattern: Massively parallel reads from many clients.
File_Type: Large, shared data files.
Latency_Sensitivity: High (for metadata operations).
Primary_Requirement: Maximum aggregate throughput.
Which storage protocol is best suited for this workload?
A) An object-based storage system using S3.
B) A standard file-based system using NFS.
C) A parallel file system like BeeGFS or Lustre.
D) A block-based protocol using iSCSI.
4. An AI team is planning two separate projects. The architect needs to provision the appropriate infrastructure for each.
| | Project A | Project B|
| -- | | - |
| Goal | Build a novel image recognition model from scratch.
| Adapt an existing, pre- trained LLM to understand company-specific jargon. |
| Input Data | 10 million new, unlabeled images. | A 50 GB text corpus of internal documents. |
| Required Compute | Very High (Weeks of multi-GPU training) | Moderate (Hours of single-GPU training) | Which two statements accurately describe the infrastructure requirements for these projects?
(Choose two.)
A) Both projects should use NetApp StorageGRID as the primary storage for training to ensure low latency.
B) Project A requires only a large amount of data, while Project B requires only a large amount of code.
C) Project A is a model building task and requires a significantly larger and more powerful compute and storage infrastructure than Project B.
D) Project B is a fine-tuning task, which leverages an existing model and requires less data and compute resources than building a model from scratch.
E) Both projects are examples of fine-tuning and have similar infrastructure needs.
5. A university is building a shared AI research platform. They have two primary requirements:
1. Performance: A "hot" research area for active model training and development that requires the absolute lowest latency and highest throughput to support multiple, simultaneous GPU- intensive jobs.
The data in this area is around 50 TB.
2. Capacity & Cost: A "cold" data lake to store over 5 PB of raw, unstructured experimental data that is infrequently accessed but must be retained for compliance and future use. This tier must be as costeffective as possible.
Which combination of NetApp hardware and technologies should an architect select to build a complete, optimized, and cost-effective solution? (Select all that apply.)
A) Use NetApp StorageGRID to build the 5 PB cost-effective data lake.
B) Enable GPUDirect Storage on the ASA system to provide the lowest latency data path to the GPUs.
C) Implement NetApp FabricPool to automatically tier inactive data from the ASA system to the StorageGRID data lake.
D) Use a NetApp All-SAN Array (ASA) system for the 50 TB high-performance "hot" research area.
E) Use a standard 10GbE network for all connectivity to reduce costs.
F) Use NetApp E-Series systems for both the hot tier and the cold data lake to simplify management.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: C,D | Question # 5 Answer: A,B,C,D |
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