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Exam Code: H13-336_V1.0
Exam Name: HCIE-AI Developer V1.0
Certification Provider: Huawei
Corresponding Certification: Huawei-certification
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H13-336_V1.0

Check Updated on: Jul 29, 2026

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Huawei H13-336_V1.0 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Model Deployment and Inference Optimization15%-20%- Inference engine and service deployment
  • 1. Batch processing and pipeline parallelism
    • 2. Edge-cloud collaborative deployment
      - Performance optimization and stability assurance
      • 1. Inference latency and throughput tuning
        • 2. Resource scheduling and fault tolerance
          Topic 2: 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. Data quality assessment and governance
                • 2. Large-scale dataset construction
                  Topic 3: Intelligent Application Development15%-20%- Agent and multi-modal application development
                  • 1. Tool calling and task planning
                    • 2. Multi-modal fusion and service integration
                      - RAG system design and implementation
                      • 1. Vector database selection and retrieval optimization
                        • 2. Prompt engineering and generation control
                          Topic 4: 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 compression, quantization and pruning
                                • 2. Model training, evaluation and selection
                                  Topic 5: AI Security and Governance5%-10%- Compliance and lifecycle governance
                                  • 1. Model audit and interpretability
                                    • 2. Compliance with AI industry regulations
                                      - Model security and privacy protection
                                      • 1. Data desensitization and federated learning
                                        • 2. Adversarial attack and defense
                                          Topic 6: 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

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