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HP HPE2-B08 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Architecting HPE Private Cloud AI Solutions | 20% | - Explain the HPE Private Cloud AI sizing and configuration guidelines - Describe how HPE Private Cloud AI supports AI/ML workloads - Explain common AI use cases and how they map to workloads - Identify components of the HPE Private Cloud AI architecture - Describe the AI/ML lifecycle and data pipeline requirements |
| Installing and Configuring HPE Private Cloud AI Solutions | 30% | - Describe the prerequisites for installing HPE Private Cloud AI - Identify the steps to configure the HPE Private Cloud AI environment - Identify how to access and use HPE Private Cloud AI management interfaces - Explain how to deploy and configure HPE Private Cloud AI components - Describe how to validate the HPE Private Cloud AI installation |
| Managing and Operating HPE Private Cloud AI Solutions | 30% | - 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 - Identify how to manage storage and data resources - Explain backup and recovery procedures - Explain how to monitor HPE Private Cloud AI performance and health |
| Supporting HPE Private Cloud AI Solutions | 20% | - Explain how to work with HPE support services - Describe support resources and documentation - Describe capacity planning and optimization best practices - Identify how to perform firmware and software updates |
HPE Private Cloud AI Solutions Sample Questions:
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?
- A. AI Pro
- B. AI Beginner
- C. AI Curious
- D. Early AI user
Correct Answer: A 🗳️
A customer is using the NVIDIA NeMo framework within HPE Private Cloud AI to build a custom generative AI application. They need to fine-tune a foundation model using a proprietary dataset. They also want to ensure the final application does not produce toxic content or veer into off-topic conversations.
Which specific toolkits within the NeMo framework should they use to achieve these two distinct goals?
(Choose 2.)
- A. NeMo Customizer
- B. NeMo Evaluator
- C. NeMo Curator
- D. NeMo Guardrails
- E. NeMo Retriever
Correct Answer: A,D 🗳️
A customer is building an application to classify images of defective products on a manufacturing line.
Which type of neural network layer is essential for this model to automatically learn and identify visual features like edges, corners, and textures in the images?
- A. A convolutional layer
- B. An output layer with a softmax function
- C. A dense (fully connected) layer
- D. A recurrent layer
Correct Answer: A 🗳️
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?
- A. NIM directly connects to the raw data sources to perform data preparation and cleaning.
- B. NIM automatically fine-tunes the model on new data to improve its accuracy.
- C. NIM provisions the underlying Kubernetes cluster and physical servers.
- D. NIM provides a framework that packages the model into an optimized, ready-to-deploy container with a standard API.
Correct Answer: D 🗳️
What is the primary architectural advantage of the NVIDIA Grace Hopper Superchip (e.g., GH200) for large-scale AI workloads?
- A. It replaces the need for server memory (DRAM) by using the GPU's global memory exclusively.
- B. It uses on-chip encryption to create a confidential computing environment for the CPU.
- C. It combines a CPU and a GPU on a single superchip, connected by a high-speed, low-latency NVLink-C2C interconnect.
- D. It is the first NVIDIA GPU to feature fourth-generation Tensor Cores for enhanced matrix calculations.
Correct Answer: C 🗳️
