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Huawei H13-325_V1.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| ModelArts AI Development Platform | 4% | - Model development, training, and deployment - ModelArts architecture and functions - Data processing and management |
| Natural Language Processing Theory and Applications | 10% | - Text classification, sentiment analysis, NER - NLP fundamentals - Word embedding and language models - Sequence models for NLP - Text preprocessing and feature engineering |
| NLP Lab Practices | 10% | - NLP model building and training - Text processing and analysis - NLP application development |
| Neural Network Basics | 4% | - Artificial neural networks - Deep feedforward networks - Deep learning fundamentals - Backpropagation algorithms - Neural network architecture design |
| Image Processing Lab Practices | 12% | - End-to-end image application development - CNN model development on ModelArts - Image processing with Python and OpenCV |
| Huawei AI Development Strategy and Portfolio | 2% | - Full-stack, all-scenario AI solutions - Huawei Cloud EI services overview |
| Image Processing Theory and Applications | 26% | - Image classification, detection, segmentation - Digital image processing basics - Feature extraction and traditional algorithms - Basic image processing tasks - Computer vision overview - Convolutional Neural Networks (CNN) - Image preprocessing techniques |
| Integrated AI Application Development | 12% | - End-to-end AI project design - ModelArts-based full lifecycle development - Application integration and optimization |
| Speech Processing Lab Practices | 10% | - Speech model training and optimization - Speech feature extraction - Speech application deployment |
| Speech Processing Theory and Applications | 10% | - Speech recognition and synthesis applications - Deep neural network models for speech - Traditional speech models (GMM, HMM) - Speech processing overview - RNN, LSTM, and advanced speech models |
