Huawei HCIE-AI Developer V1.0 : H13-336_V1.0 Exam

  • Exam Code: H13-336_V1.0
  • Exam Name: HCIE-AI Developer V1.0
  • Updated: Aug 17, 2026
  • Q & A: 0 Questions and Answers

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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: AI Development Fundamentals and Large Model Technologies15%-20%- Advanced machine learning and deep learning principles
          • 1. Neural network optimization and regularization
            • 2. Foundation model architectures (Transformer, MoE, etc.)
              - Large model pre-training and alignment technologies
              • 1. Pre-training data construction and processing
                • 2. Fine-tuning, RLHF, DPO and other alignment methods
                  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: Intelligent Application Development15%-20%- RAG system design and implementation
                          • 1. Prompt engineering and generation control
                            • 2. Vector database selection and retrieval optimization
                              - Agent and multi-modal application development
                              • 1. Tool calling and task planning
                                • 2. Multi-modal fusion and service integration
                                  Topic 5: 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 6: Huawei AI Platform and Model Development25%-30%- MindSpore framework and Ascend computing system
                                          • 1. Operator development and optimization
                                            • 2. Distributed training strategies
                                              - ModelArts full-lifecycle development
                                              • 1. Model compression, quantization and pruning
                                                • 2. Model training, evaluation and selection

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