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| Section | Weight | Objectives |
|---|---|---|
| Installing and Configuring HPE Private Cloud AI Solutions | 30% | - Explain how to deploy and configure HPE Private Cloud AI components - 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 - Identify the steps to configure the HPE Private Cloud AI environment |
| Supporting HPE Private Cloud AI Solutions | 20% | - Describe support resources and documentation - Identify how to perform firmware and software updates - Explain how to work with HPE support services - Describe capacity planning and optimization best practices |
| Architecting HPE Private Cloud AI Solutions | 20% | - Explain the HPE Private Cloud AI sizing and configuration guidelines - Explain common AI use cases and how they map to workloads - Describe the AI/ML lifecycle and data pipeline requirements - Identify components of the HPE Private Cloud AI architecture - Describe how HPE Private Cloud AI supports AI/ML workloads |
| Managing and Operating HPE Private Cloud AI Solutions | 30% | - Explain how to monitor HPE Private Cloud AI performance and health - Explain backup and recovery procedures - Identify how to manage storage and data resources - Describe the tools and methods for managing HPE Private Cloud AI - Describe how to manage users and access control - Identify troubleshooting procedures and common issues |
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NEW QUESTION # 33
A customer in the public sector wants to use AI to analyze live video feeds from city-wide cameras to automate public safety tasks like detecting traffic accidents or identifying security threats in real-time.
This is their first major AI initiative.
Which AI use case does this scenario represent?
Answer: D
NEW QUESTION # 34
You are in a meeting with the VP of Manufacturing for a large industrial company. She describes their AI program as follows:
"We have a formal Center of Excellence for AI that reports directly to the CTO. Our strategy is to scale our successful predictive maintenance models across all 25 of our global plants. We have standardized on a consistent cloud and data governance strategy for all AI projects and have clear ROI targets for reducing downtime." Based on this description, which AI maturity level best describes this customer?
Answer: A
NEW QUESTION # 35
A company has developed a custom fraud detection model. Their data science team wants to deploy this model into production for other applications to use. They want to avoid the complexity of manually configuring the serving environment, optimizing for hardware, and creating a scalable API endpoint.
How does using an NVIDIA Inference Microservice (NIM) within HPE Private Cloud AI simplify this process?
Answer: A
NEW QUESTION # 36
A customer wants to deploy a turnkey private cloud for a variety of generative AI workloads, including RAG-based chatbots and some model fine-tuning. One of their key IT stakeholders is the data engineer.
Which specific challenge for a data engineer is directly addressed by the HPE Data Fabric component within HPE Private Cloud AI?
Answer: A
NEW QUESTION # 37
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: C
NEW QUESTION # 38
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