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HP HPE0-V31 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: HPE Private Cloud AI Solution Design30%- Configuration and Quoting
  • 1. Size solutions using HPE tools
  • 2. Match infrastructure to AI workload requirements
  • 3. Configure and quote AI solutions
- Architecture and Infrastructure
  • 1. HPE Private Cloud AI architecture
  • 2. Storage and networking components
  • 3. Infrastructure sizing and workload mapping
  • 4. HPE AI servers and NVIDIA GPU platforms
Topic 2: AI Overview and Customer Requirements25%- Customer Assessment
  • 1. Analyze AI workloads and use cases
  • 2. Assess customer AI maturity
  • 3. Position HPE and NVIDIA AI solutions
- AI Fundamentals
  • 1. Machine learning and deep learning lifecycle
  • 2. Artificial intelligence concepts and ecosystem
  • 3. AI challenges and considerations
Topic 3: AI Deployment and Operations25%- Model Serving and AI Workloads
  • 1. Use model catalogs and knowledge bases
  • 2. Implement HPE Machine Learning Inference Software
  • 3. Deploy models using NVIDIA NIMs
- Platform Deployment
  • 1. Use HPE AI Essentials resource management
  • 2. Deploy and configure HPE Private Cloud AI
  • 3. Manage AI administrator and user environments
- Operations and Maintenance
  • 1. Monitor AI platform health and performance
  • 2. Perform software updates and lifecycle management
  • 3. Troubleshoot AI environments
Topic 4: Edge AI and HPC Solutions20%- HPC and AI Convergence
  • 1. HPE HPC management tools
  • 2. HPC fundamentals and AI integration
  • 3. HPE HPC compute portfolio
  • 4. HPE Cray XD and HPE ProLiant XD platforms
- Edge Inferencing
  • 1. Implement AI-optimized edge architectures
  • 2. Design edge inferencing solutions
  • 3. Select appropriate servers, GPUs, and networking

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