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HP HPE3-CL10 Exam Syllabus Topics:

SectionObjectives
Topic 1: AI Workloads and Use Cases- Enterprise AI adoption
  • 1. Data pipeline considerations
    • 2. Model lifecycle overview
      - Industry AI applications
      • 1. Computer vision workloads
        • 2. Natural language processing workloads
          Topic 2: HPE AI Infrastructure and Solutions- AI deployment environments
          • 1. Hybrid AI environments
            • 2. On-premises AI infrastructure
              - HPE AI portfolio overview
              • 1. AI-ready infrastructure design principles
                • 2. HPE GPU-accelerated systems
                  Topic 3: NVIDIA AI Computing Fundamentals- Core concepts of accelerated computing
                  • 1. CPU vs GPU architecture overview
                    • 2. Parallel processing concepts
                      - AI and machine learning workload basics
                      • 1. Training vs inference workloads
                        • 2. Common AI workload types
                          Topic 4: GPU Architecture and Accelerated Computing- Performance optimization concepts
                          • 1. Scaling AI workloads across GPUs
                            • 2. Throughput vs latency considerations
                              - NVIDIA GPU fundamentals
                              • 1. GPU memory and compute architecture basics
                                • 2. CUDA and acceleration concepts
                                  Topic 5: AI Operations and Deployment- Infrastructure operations
                                  • 1. Resource allocation in GPU clusters
                                    • 2. Monitoring AI workloads
                                      - Security and governance basics
                                      • 1. Data governance considerations
                                        • 2. AI infrastructure security principles

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