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Huawei H13-321_V2.0 (HCIP-AI-EI Developer V2.0) Certification Exam is an excellent way for IT professionals to validate their skills and knowledge in the field of AI and EI. It is a globally recognized certification that can help professionals to advance their careers and stand out in a competitive job market.
Huawei H13-321_V2.0 certification exam covers a wide range of topics related to AI and EI development, including machine learning, deep learning, natural language processing, and computer vision. H13-321_V2.0 exam also covers topics related to data processing, model deployment, and performance evaluation. HCIP-AI-EI Developer V2.0 certification exam is designed to test the candidate's ability to design, develop, and implement AI and EI solutions that meet the business requirements of organizations.
Huawei H13-321_V2.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Overview of ModelArts | 4% | - ModelArts platform positioning and architecture - Data processing, training, deployment capabilities - Development environment and tool usage |
| Image Processing Theory and Applications | 26% | - Convolutional Neural Networks (CNN) - Image processing fundamentals - Image classification, object detection, segmentation - OCR and visual application development |
| Speech Processing Lab Guide | 12% | - Huawei Cloud Speech Interaction Service - ModelArts speech application deployment - ASR and TTS service development |
| Speech Processing Theory and Applications | 10% | - Automatic Speech Recognition (ASR) - Speech signal characteristics and processing - Text-to-Speech (TTS) technology - Acoustic and language modeling |
| Image Processing Lab Guide | 12% | - ModelArts-based image classification - Ascend-based deployment - Object detection and segmentation practice |
| Natural Language Processing Lab Guide | 10% | - ModelArts NLP model training and tuning - Application integration and deployment - Text classification and NER implementation |
| Huawei AI Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | - Huawei AI development strategy - Full-stack and all-scenario AI technology layout |
| Natural Language Processing Theory and Applications | 10% | - Word representation and embedding - RNN, LSTM, GRU, Transformer architecture - Text classification, NER, machine translation - BERT, GPT and pre-trained models |
| Neural Network Basics | 4% | - Basic concepts of neural networks - Activation functions and regularization - Multilayer Perceptron (MLP) - Gradient descent and backpropagation |
