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HP HPE0-V30 : HPE AI Fundamentals

HPE0-V30 real exams

Exam Code: HPE0-V30

Exam Name: HPE AI Fundamentals

Updated: Aug 17, 2026

Q & A: 0 Questions and Answers

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HP HPE0-V30 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Fundamentals and Business Value25%- AI Concepts
  • 1. Identify common AI workloads and use cases
  • 2. Define artificial intelligence, machine learning, deep learning, and generative AI
- AI Adoption
  • 1. Identify AI opportunities and business outcomes
  • 2. Assess customer AI maturity
  • 3. Position HPE AI solutions based on customer requirements
Topic 2: AI Infrastructure Deployment and Management25%- Optimization and Troubleshooting
  • 1. Optimize performance of compute and AI solutions
  • 2. Troubleshoot AI and compute environments
- Storage and Virtualization
  • 1. Deploy HPE VM Essentials environments
  • 2. Design storage solutions for AI and compute workloads
  • 3. Describe HPE VM Essentials features and benefits
- Edge and Inferencing Solutions
  • 1. Select appropriate servers, GPUs, and networking components
  • 2. Design edge inferencing solutions
- Compute Management
  • 1. Apply best practices for HPE ProLiant deployments
  • 2. Manage server lifecycle and firmware updates
  • 3. Use HPE Compute Ops Management
Topic 3: AI Solution Planning and Operations25%- Solution Configuration
  • 1. Configure and quote HPE Private Cloud AI solutions
  • 2. Select appropriate services and support offerings
- GreenLake Services
  • 1. Manage updates, performance, and operational requests
  • 2. Use HPE GreenLake cloud services for AI environments
- Customer Engagement
  • 1. Understand customer and HPE responsibilities
  • 2. Use Customer Intent Documents
  • 3. Address changing customer requirements and solution expansion
- Demonstrations
  • 1. Demonstrate a basic AI use case using HPE Private Cloud AI
Topic 4: HPE Private Cloud AI Architecture25%- Infrastructure Components
  • 1. Identify benefits of HPE and NVIDIA infrastructure components
  • 2. Describe HPE Private Cloud AI with NVIDIA architecture
  • 3. Explain compute, GPU, networking, and storage requirements for AI workloads
- Sizing
  • 1. Size HPE Private Cloud AI solutions using customer requirements and HPE tools
- Software Components
  • 1. Explain benefits of HPE and NVIDIA software solutions
  • 2. Describe software stack elements used in HPE Private Cloud AI

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