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HP HPE3-CL10 Exam Syllabus Topics:

SectionObjectives
AI Operations and Deployment- Security and governance basics
  • 1. AI infrastructure security principles
    • 2. Data governance considerations
      - Infrastructure operations
      • 1. Monitoring AI workloads
        • 2. Resource allocation in GPU clusters
          HPE AI Infrastructure and Solutions- HPE AI portfolio overview
          • 1. HPE GPU-accelerated systems
            • 2. AI-ready infrastructure design principles
              - AI deployment environments
              • 1. On-premises AI infrastructure
                • 2. Hybrid AI environments
                  NVIDIA AI Computing Fundamentals- AI and machine learning workload basics
                  • 1. Common AI workload types
                    • 2. Training vs inference workloads
                      - Core concepts of accelerated computing
                      • 1. Parallel processing concepts
                        • 2. CPU vs GPU architecture overview
                          AI Workloads and Use Cases- Enterprise AI adoption
                          • 1. Model lifecycle overview
                            • 2. Data pipeline considerations
                              - Industry AI applications
                              • 1. Natural language processing workloads
                                • 2. Computer vision workloads
                                  GPU Architecture and Accelerated Computing- NVIDIA GPU fundamentals
                                  • 1. GPU memory and compute architecture basics
                                    • 2. CUDA and acceleration concepts
                                      - Performance optimization concepts
                                      • 1. Throughput vs latency considerations
                                        • 2. Scaling AI workloads across GPUs

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