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Huawei H13-311_V3.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Machine Learning Overview | 20% | - Basic concepts and workflow of machine learning - Supervised, unsupervised and reinforcement learning - Common algorithms and model evaluation methods |
| Huawei Open AI Platform for Smart Devices | 2% | - Platform positioning and capabilities - Edge AI application development |
| Deep Learning Overview | 20% | - Convolutional neural networks and recurrent neural networks - Neural network basics - Training, optimization and application of deep learning models |
| AI Overview | 10% | - Huawei full-stack all-scenario AI strategy - Technical system and application scenarios of AI - Definition and development history of AI |
| Comprehensive AI Experiment | 17% | - End-to-end AI development workflow - Model training, tuning and deployment practice |
| Huawei AI Computing Platform Atlas | 5% | - Ascend AI processor architecture - Atlas series hardware and software ecosystem |
| Huawei AI Development Framework MindSpore | 3% | - Model development and deployment using MindSpore - MindSpore core concepts and architecture |
| Mainstream AI Development Frameworks | 18% | - TensorFlow architecture and features - Comparison and selection of development frameworks - PyTorch architecture and features |
| HUAWEI CLOUD Enterprise Intelligence Application Platform | 5% | - EI service portfolio and features - AI solution deployment on Huawei Cloud |
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