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Huawei H13-336_V1.0 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Development Fundamentals and Large Model Technologies15%-20%- Large model pre-training and alignment technologies
  • 1. Pre-training data construction and processing
    • 2. Fine-tuning, RLHF, DPO and other alignment methods
      - Advanced machine learning and deep learning principles
      • 1. Neural network optimization and regularization
        • 2. Foundation model architectures (Transformer, MoE, etc.)
          Topic 2: Huawei AI Platform and Model Development25%-30%- ModelArts full-lifecycle development
          • 1. Model training, evaluation and selection
            • 2. Model compression, quantization and pruning
              - MindSpore framework and Ascend computing system
              • 1. Operator development and optimization
                • 2. Distributed training strategies
                  Topic 3: Data Engineering for AI10%-15%- Feature engineering and data management
                  • 1. Feature selection, transformation and encoding
                    • 2. Data version control and lifecycle management
                      - Data collection, cleaning and annotation
                      • 1. Large-scale dataset construction
                        • 2. Data quality assessment and governance
                          Topic 4: Model Deployment and Inference Optimization15%-20%- Performance optimization and stability assurance
                          • 1. Resource scheduling and fault tolerance
                            • 2. Inference latency and throughput tuning
                              - Inference engine and service deployment
                              • 1. Edge-cloud collaborative deployment
                                • 2. Batch processing and pipeline parallelism
                                  Topic 5: AI Security and Governance5%-10%- Compliance and lifecycle governance
                                  • 1. Compliance with AI industry regulations
                                    • 2. Model audit and interpretability
                                      - Model security and privacy protection
                                      • 1. Adversarial attack and defense
                                        • 2. Data desensitization and federated learning
                                          Topic 6: Intelligent Application Development15%-20%- RAG system design and implementation
                                          • 1. Vector database selection and retrieval optimization
                                            • 2. Prompt engineering and generation control
                                              - Agent and multi-modal application development
                                              • 1. Tool calling and task planning
                                                • 2. Multi-modal fusion and service integration
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