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Huawei H13-321_V2.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Speech Processing Theory and Applications | 10% | - Automatic Speech Recognition (ASR) - Speech signal characteristics and processing - Text-to-Speech (TTS) technology - Acoustic and language modeling |
| Topic 2: Natural Language Processing Lab Guide | 10% | - ModelArts NLP model training and tuning - Application integration and deployment - Text classification and NER implementation |
| Topic 3: Image Processing Lab Guide | 12% | - Object detection and segmentation practice - ModelArts-based image classification - Ascend-based deployment |
| Topic 4: Huawei AI Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | - Full-stack and all-scenario AI technology layout - Huawei AI development strategy |
| Topic 5: Natural Language Processing Theory and Applications | 10% | - RNN, LSTM, GRU, Transformer architecture - Text classification, NER, machine translation - BERT, GPT and pre-trained models - Word representation and embedding |
| Topic 6: Neural Network Basics | 4% | - Activation functions and regularization - Multilayer Perceptron (MLP) - Gradient descent and backpropagation - Basic concepts of neural networks |
| Topic 7: Speech Processing Lab Guide | 12% | - Huawei Cloud Speech Interaction Service - ModelArts speech application deployment - ASR and TTS service development |
| Topic 8: Overview of ModelArts | 4% | - ModelArts platform positioning and architecture - Development environment and tool usage - Data processing, training, deployment capabilities |
| Topic 9: Image Processing Theory and Applications | 26% | - Convolutional Neural Networks (CNN) - Image classification, object detection, segmentation - OCR and visual application development - Image processing fundamentals |
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
1. When taking photos against the light, the face is relatively dark. Use gamma correction to enhance the image to achieve a clear effect even in backlight. What value of can be selected?
A) 0
B) 1
C) 0.5
D) 2
2. What does the REST API request/response contain? (Multiple choice)
A) Request message header
B) Request URL
C) Response message body
D) Request message body
E) Response message header
3. In order to effectively convert digital images into structured data, image feature extraction technology is needed to reduce the dimension of the data.
Which of the following are the main ideas for image feature extraction and data dimensionality reduction? (Multiple choice)
A) Downsampling
B) Pattern recognition
C) Feature Descriptor
D) Segmentation of Region of Interest
4. Which of the following belongs to the language model?
A) DT
B) N-gram
C) GT
D) Adaboost
5. Challenges of traditional machine learning include the curse of dimensionality.
A) False
B) True
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: A,B,C,D,E | Question # 3 Answer: A,C,D | Question # 4 Answer: B | Question # 5 Answer: B |
