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Last Updated: Aug 17, 2026
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Managing and Operating HPE Private Cloud AI Solutions | 30% | - Identify troubleshooting procedures and common issues - Describe the tools and methods for managing HPE Private Cloud AI - Explain how to monitor HPE Private Cloud AI performance and health - Identify how to manage storage and data resources - Describe how to manage users and access control - Explain backup and recovery procedures |
| Topic 2: Installing and Configuring HPE Private Cloud AI Solutions | 30% | - Identify how to access and use HPE Private Cloud AI management interfaces - Explain how to deploy and configure HPE Private Cloud AI components - Describe the prerequisites for installing HPE Private Cloud AI - Identify the steps to configure the HPE Private Cloud AI environment - Describe how to validate the HPE Private Cloud AI installation |
| Topic 3: Supporting HPE Private Cloud AI Solutions | 20% | - Identify how to perform firmware and software updates - Describe support resources and documentation - Describe capacity planning and optimization best practices - Explain how to work with HPE support services |
| Topic 4: Architecting HPE Private Cloud AI Solutions | 20% | - 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 the AI/ML lifecycle and data pipeline requirements - Describe how HPE Private Cloud AI supports AI/ML workloads |
1. An architect is presenting to a customer who is an 'Early AI User'. The customer is unsure about the differences between their two main project ideas.
Project 1: Create an internal chatbot that can answer HR policy questions by accessing the live employee handbook stored on a shared drive.
Project 2: Teach a general-purpose chatbot to adopt the company's formal communication style and tone for drafting official press releases.
How should the architect categorize the primary AI task for each project? (Choose 2.)
A) Project 1 is a model training workload.
B) Project 2 is a classic inferencing workload with no model customization.
C) Project 2 is a fine-tuning workload.
D) Project 1 is a RAG (Retrieval-Augmented Generation) workload.
2. A customer in the media and entertainment industry wants a solution to accelerate the creation of 3D animations and renderings. Their artists need to be able to generate complex visual AI content quickly.
The company has a mature AI practice and requires a powerful, data center-based solution.
Which HPE ProLiant server and NVIDIA GPU combination is purpose-built for these generative visual AI workloads?
A) HPE ProLiant DL320 Gen11 server with NVIDIA L4 GPUs
B) HPE ProLiant DL380a Gen11 server with CPU-only configuration
C) HPE ProLiant DL380a Gen12 server with an NVIDIA NVLink Bridge but no GPUs
D) HPE ProLiant DL380a Gen11 server with NVIDIA L40S GPUs
3. An IT director for a regional retail chain tells you they are "doing AI." Upon further questioning, you learn they have one data scientist who has built a single, experimental sales forecasting model as a proof-of-concept (PoC). The project lacks clear KPIs for success and there is no formal strategy for how to productionize it or what to do next.
How would you classify this customer's AI maturity level?
A) Deployer of AI at scale
B) AI Curious
C) AI Pro
D) AI Beginner
4. What is the primary purpose of using the "Private Cloud Smart Template" within HPE One Config Advanced (OCA) when quoting an HPE Private Cloud AI solution?
A) To ensure a fast, easy, and validated process for generating a complete and accurate Bill of Materials (BOM) for a pre-integrated solution.
B) To automatically generate a network diagram and rack elevation for the customer.
C) To provide a free trial license for the VMware and NVIDIA software.
D) To allow for complete customization of every component, including unsupported hardware.
5. A large financial institution, a known "Deployer of AI at scale," needs to train a next-generation fraud detection model. This new model has over a trillion parameters, significantly larger than their current models, and requires an exascale-class computing solution to be trained in a reasonable timeframe.
Which HPE AI solution should be positioned to meet this customer's demanding requirement?
A) AI-optimized HPE ProLiant DL servers
B) HPE Cray systems
C) HPE Private Cloud AI with NVIDIA, Large configuration
D) HPE GreenLake for File Storage
Solutions:
| Question # 1 Answer: C,D | Question # 2 Answer: D | Question # 3 Answer: D | Question # 4 Answer: A | Question # 5 Answer: B |
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