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HP HPE0-V31 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Edge AI and HPC Solutions20%- Edge Inferencing
  • 1. Select appropriate servers, GPUs, and networking
  • 2. Implement AI-optimized edge architectures
  • 3. Design edge inferencing solutions
- 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
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. AI challenges and considerations
  • 2. Artificial intelligence concepts and ecosystem
  • 3. Machine learning and deep learning lifecycle
Topic 3: HPE Private Cloud AI Solution Design30%- 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
- Configuration and Quoting
  • 1. Size solutions using HPE tools
  • 2. Match infrastructure to AI workload requirements
  • 3. Configure and quote AI solutions
Topic 4: AI Deployment and Operations25%- Platform Deployment
  • 1. Manage AI administrator and user environments
  • 2. Deploy and configure HPE Private Cloud AI
  • 3. Use HPE AI Essentials resource management
- Operations and Maintenance
  • 1. Troubleshoot AI environments
  • 2. Perform software updates and lifecycle management
  • 3. Monitor AI platform health and performance
- Model Serving and AI Workloads
  • 1. Implement HPE Machine Learning Inference Software
  • 2. Use model catalogs and knowledge bases
  • 3. Deploy models using NVIDIA NIMs

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