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Huawei-certification H13-336_V1.0

H13-336_V1.0

Exam Code: H13-336_V1.0

Exam Name: HCIE-AI Developer V1.0

Updated: Sep 16, 2026

Q&A Number: 0 Q&As

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Huawei H13-336_V1.0 Exam Syllabus Topics:

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

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