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| Section | Weight | Objectives |
|---|---|---|
| AI Overview | 15% | - AI industry use cases and applications - Convergence of AI, high-performance computing, and analytics - Algorithm types: supervised, unsupervised, reinforcement learning - AI deployment models: on-premises, cloud, edge - AI, machine learning, and deep learning concepts |
| NetApp AI Solutions and Architecture | 25% | - ONTAP integration with AI frameworks - Scalability and performance optimization for AI - Storage architectures for AI workloads - NetApp AI-ready infrastructure components - Data management and data pipeline design |
| Security, Reliability, and Operations | 15% | - High availability and data protection - Cost management and efficiency - Monitoring, logging, and troubleshooting AI environments - Data security and access control for AI |
| Cloud and Hybrid Cloud AI Deployment | 18% | - Hybrid and multi-cloud AI architectures - NetApp cloud data services for AI - Data mobility and consistency across environments - Cloud-native AI solutions and integration |
| AI Lifecycle | 27% | - AI governance, ethics, and compliance - Model training, inference, and optimization - AI lifecycle stages: design, training, deployment, monitoring - Predictive vs generative AI - Data preparation and management for AI |
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NEW QUESTION # 104
A data scientist is using the NetApp DataOps Toolkit for Python to automate the creation of a new, writable volume for an experiment. The script is intended to clone an existing dataset volume. When the script is executed, it fails with an error.
The relevant portion of the Python script is:
from netapp_dataops.k8s import clone_pvc
clone_pvc(
source_pvc_name="dataset-v1-pvc",
new_pvc_name="experiment-clone-pvc",
namespace="ds-team-1"
)
The script produces the following error in the terminal:
'Error: Failed to clone PVC. Source PVC 'dataset-v1-pvc' not found in namespace 'ds-team-1'.' What is the most likely cause of this error?
Answer: A
NEW QUESTION # 105
Due to the success of the "Advisor Assistant," the number of concurrent users is expected to double in the next quarter. The existing Kubernetes cluster is running at 80% of its GPU capacity during peak hours. The architect must propose a plan to scale the compute infrastructure to handle the increased load.
Which two strategies represent the most effective and scalable solutions? (Choose 2.)
Answer: D,E
NEW QUESTION # 106
Which of the following platforms provides tools for model training and deployment specifically for AI workloads?
Answer: B
NEW QUESTION # 107
A new team of external auditors requires read-only access to the raw financial product documentation stored in the StorageGRID data lake. The data is in a bucket named 'prod-docs'.
The security team must ensure the auditors can list and read objects but cannot write, delete, or modify any data. Which is the most appropriate method to grant this specific access?
Answer: D
NEW QUESTION # 108
The firm has acquired a competitor, and the volume of proprietary documents for the "Advisor Assistant" is expected to triple, exceeding the capacity of the current StorageGRID data lake. The architect needs to expand the data lake's capacity non-disruptively.
The current StorageGRID status is:
System_Health: Nominal
Node_Count: 6 (3 Storage Nodes, 3 Admin/Gateway Nodes)
Usable_Capacity: 1.5 PB
Used_Capacity: 1.4 PB (93%)
What is the standard procedure for scaling the capacity of the on-premises NetApp StorageGRID system?
Answer: C
NEW QUESTION # 109
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