Network Appliance NetApp Certified AI Expert NS0-901

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Network Appliance NetApp Certified AI Expert 認定 NS0-901 試験問題:

1. A robotics company is developing a control system for an autonomous warehouse drone. The drone must learn to navigate complex environments to pick up packages. The development team has created a physics-based simulation where the drone can attempt the task millions of times.
The drone receives a positive reward for successfully retrieving a package and a negative penalty for collisions. Which type of machine learning algorithm is being used in this scenario?

A) Supervised learning
B) Unsupervised learning
C) Reinforcement learning
D) Generative learning

2. An architect is designing a fully automated, end-to-end MLOps pipeline on Kubernetes for a computer vision use case. The pipeline must handle everything from data versioning to model deployment.
The required pipeline stages are:
1. Data Versioning: Create a new, immutable version of the master dataset for the pipeline run.
2. Data Preparation: Launch a pod to run a preprocessing script on the versioned data.
3. Model Training: Launch a distributed training job that reads the prepared data from a highperformance volume.
4. Model Deployment: Push the trained model to a production inference service.
Which combination of NetApp and Kubernetes technologies provides the most effective and automated solution for this entire pipeline?

A) Use NetApp SnapMirror for data versioning and manually create hostPath volumes for each pipeline stage.
B) Use a single, large ReadWriteMany PVC for all stages to simplify the pipeline configuration.
C) Manually create a NetApp Snapshot via System Manager before each pipeline run, and use the NetApp DataOps Toolkit only for the training stage.
D) Use NetApp XCP to copy the data for each stage and configure static PersistentVolumes for each pod.
E) Use the NetApp DataOps Toolkit to create a Snapshot of the source data volume (for versioning), then create a FlexClone PVC from the snapshot for the preparation stage, and finally create a FlexGroup PVC for the training stage.

3. 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) Both projects are examples of fine-tuning and have similar infrastructure needs.
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 A requires only a large amount of data, while Project B requires only a large amount of code.
E) 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.

4. An architect is designing a comprehensive AI platform for a large enterprise. The platform must support the entire data lifecycle, from ingest at the edge to a central data lake, and finally to a high- performance training cluster.
The requirements are:
- Edge Ingest: Data must be collected at remote sites and efficiently replicated to the core.
- Data Lake: A central, petabyte-scale repository for unstructured data, accessible via the S3 protocol.
- Training Cluster: A high-performance compute cluster that requires low-latency, parallel file access to training datasets.
- Data Traceability: All datasets used for training must be immutably versioned.
Which combination of NetApp technologies and protocols should the architect choose to build this solution? (Select all that apply.)

A) Use iSCSI as the primary protocol for the data lake to ensure maximum compatibility.
B) Use NetApp Snapshots on the training dataset volumes to create immutable, point-in-time versions for traceability.
C) Use NetApp FlexCache to tier cold data from the data lake to the public cloud.
D) Use NetApp ONTAP systems at the edge and NetApp SnapMirror to replicate data to the core data center.
E) Use a NetApp E-Series system with a parallel file system (like BeeGFS) to provide high- performance, parallel file access for the training cluster.
F) Use NetApp StorageGRID to create the petabyte-scale, S3-accessible data lake at the core.

5. 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 SnapLock (Compliance Mode)
B) NetApp Volume Encryption (NVE)
C) Autonomous Ransomware Protection (ARP)
D) Multi-Admin Verification (MAV)

質問と回答：