Exam Name: HCIP-AI-Application Developer V1.0
Certification Provider: Huawei
Corresponding Certification: Huawei-certification
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Check Updated on: Aug 18, 2026
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Huawei H13-325_V1.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Speech Processing Lab Practices | 10% | - Speech application deployment - Speech model training and optimization - Speech feature extraction |
| Topic 2: Image Processing Lab Practices | 12% | - End-to-end image application development - Image processing with Python and OpenCV - CNN model development on ModelArts |
| Topic 3: ModelArts AI Development Platform | 4% | - Model development, training, and deployment - Data processing and management - ModelArts architecture and functions |
| Topic 4: Neural Network Basics | 4% | - Deep feedforward networks - Deep learning fundamentals - Backpropagation algorithms - Artificial neural networks - Neural network architecture design |
| Topic 5: Huawei AI Development Strategy and Portfolio | 2% | - Huawei Cloud EI services overview - Full-stack, all-scenario AI solutions |
| Topic 6: Image Processing Theory and Applications | 26% | - Image classification, detection, segmentation - Basic image processing tasks - Convolutional Neural Networks (CNN) - Feature extraction and traditional algorithms - Computer vision overview - Digital image processing basics - Image preprocessing techniques |
| Topic 7: Natural Language Processing Theory and Applications | 10% | - Word embedding and language models - NLP fundamentals - Text classification, sentiment analysis, NER - Sequence models for NLP - Text preprocessing and feature engineering |
| Topic 8: NLP Lab Practices | 10% | - NLP application development - NLP model building and training - Text processing and analysis |
| Topic 9: Integrated AI Application Development | 12% | - ModelArts-based full lifecycle development - End-to-end AI project design - Application integration and optimization |
| Topic 10: Speech Processing Theory and Applications | 10% | - Deep neural network models for speech - RNN, LSTM, and advanced speech models - Speech processing overview - Traditional speech models (GMM, HMM) - Speech recognition and synthesis applications |
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