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| Section | Weight | Objectives |
|---|---|---|
| Managing and Operating HPE Private Cloud AI Solutions | 30% | - Describe how to manage users and access control - Identify how to manage storage and data resources - Identify troubleshooting procedures and common issues - Describe the tools and methods for managing HPE Private Cloud AI - Explain backup and recovery procedures - Explain how to monitor HPE Private Cloud AI performance and health |
| Supporting HPE Private Cloud AI Solutions | 20% | - Describe capacity planning and optimization best practices - Identify how to perform firmware and software updates - Describe support resources and documentation - Explain how to work with HPE support services |
| Architecting HPE Private Cloud AI Solutions | 20% | - Describe the AI/ML lifecycle and data pipeline requirements - Explain common AI use cases and how they map to workloads - Explain the HPE Private Cloud AI sizing and configuration guidelines - Identify components of the HPE Private Cloud AI architecture - Describe how HPE Private Cloud AI supports AI/ML workloads |
| Installing and Configuring HPE Private Cloud AI Solutions | 30% | - Identify how to access and use HPE Private Cloud AI management interfaces - Describe how to validate the HPE Private Cloud AI installation - Describe the prerequisites for installing HPE Private Cloud AI - Explain how to deploy and configure HPE Private Cloud AI components - Identify the steps to configure the HPE Private Cloud AI environment |
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NEW QUESTION # 37
A customer who is an "AI Beginner" wants to start an AI inferencing project at their edge locations.
Their goal is to analyze security camera feeds to help prevent theft. They have a limited budget and IT staff at the edge sites.
Which HPE AI solution is the most appropriate to position for this specific scenario?
Answer: D
NEW QUESTION # 38
An architect is working with a customer who has been identified as an 'AI Pro'. They have a mature AI practice and are looking to scale their efforts in creating 'digital twin' simulations for automotive prototypes. This involves complex, graphics-intensive AI workloads. The customer wants a full-stack, turnkey private cloud solution to accelerate this initiative.
What is the most appropriate HPE solution to position for this customer?
Answer: A
NEW QUESTION # 39
An architect is selecting the appropriate HPE Private Cloud AI configuration for a customer. The customer's primary workload is fine-tuning a 70B parameter model, a task that is extremely sensitive to compute latency and requires the highest possible performance for multi-node distributed training.
Which specific infrastructure components included in the "Large" configuration of HPE Private Cloud AI are essential for meeting this high-performance training requirement? (Select all that apply.)
Answer: B,C,E
NEW QUESTION # 40
An architect is assessing a customer's workloads to position the correct HPE Private Cloud AI configuration. The customer has a single, massive task: training a foundational vision model from scratch using a petabyte-scale image dataset. The project is expected to take months and requires the absolute maximum compute performance available.
Which AI workload type does this represent, and which HPE solution is most appropriate?
Answer: D
NEW QUESTION # 41
A sales professional is preparing a quote for an HPE Private Cloud AI solution in OCA and needs to ensure the correct support services are attached.
What is the default level of support included with all components when using the "Flexible services" option in the Smart Template?
Answer: B
NEW QUESTION # 42
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