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Huawei H13-334_V1.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Large Model Business Scenario and Process | 15% | - End-to-end workflow of large model solutions - Industry-specific AI solution design principles - AI application scenarios and requirements analysis |
| Large Model Algorithm Architecture | 25% | - Model compression, quantization and optimization - Prompt engineering and context management - Transformer architecture and variants - Pre-training, fine-tuning and alignment technologies |
| Huawei Ascend Large Model Solution | 25% | - Distributed training and parallel strategies - Model inference and deployment on Ascend - Ascend AI processor architecture - MindSpore and MindFormers framework |
| Large Model Security and Governance | 8% | - Data privacy and compliance - Risk control and ethical considerations - Model lifecycle management - Model security and robustness |
| Huawei Intelligent Computing Center Infrastructure | 15% | - Resource scheduling and management - AI computing cluster architecture - Storage and networking for large model workloads - Energy efficiency and reliability design |
| Model Selection, Migration and Training | 12% | - Data preparation and quality control - Model selection criteria and benchmarking - Supervised fine-tuning and reinforcement learning from human feedback - Cross-platform model migration |
