Exam Name: HCIP-AI-EI Developer V2.5
Certification Provider: Huawei
Corresponding Certification: HCIP-AI EI Developer
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Check Updated on: Sep 20, 2026
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- Total Questions: 62
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Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Overview of ModelArts | 4% | - ModelArts positioning and architecture - Basic operation process - Core functions and service modules |
| Theoretical Knowledge and Applications of Image Processing | 26% | - Image classification, detection and segmentation - Typical application scenarios - Feature extraction and representation - Image preprocessing technology |
| Natural Language Processing Lab Guide | 10% | - Text preprocessing and feature engineering - End-to-end application development - NLP model training and evaluation |
| Image Processing Lab Guide | 12% | - Image processing model development and deployment - Performance optimization and testing - Development environment setup |
| Overview of Huawei's AI Development Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | - Full-stack AI technology system - Huawei AI development layout - All-scenario AI solutions |
| Speech Processing Lab Guide | 12% | - Speech model building and tuning - Speech data processing practice - Application deployment and verification |
| Neural Network Basics | 4% | - Common neural network structures - Training and optimization methods - Basic concepts of neural networks |
| Theoretical Knowledge and Applications of Natural Language Processing | 10% | - Practical application - Language model and semantic understanding - Text processing and representation - Machine translation, text generation and other technologies |
| Theoretical Knowledge and Applications of Speech Processing | 10% | - Application cases - Speech signal processing foundation - Speech recognition and synthesis - Speech feature extraction |
Huawei HCIP-AI-EI Developer V2.5 Sample Questions:
Which of the following are required for the image object detection algorithm?
- A. Object classification determination
- B. Object location calculation
- C. Confidence calculation
- D. Object contour calculation
Correct Answer: A,B,C 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
How many parameters need to be learned when a 3 × 3 convolution kernel is used to perform the convolution operation on two three-channel color images?
- A. 28
- B. 9
- C. 55
- D. 10
Correct Answer: A 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
What are the advantages of deep learning-based speech recognition algorithms?
- A. No data training
- B. Forced alignment of annotated data
- C. End-to-end task processing
- D. Automated feature extraction
Correct Answer: C,D 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
The attention mechanism in foundation model architectures allows the model to focus on specific parts of the input data. Which of the following steps are key components of a standard attention mechanism?
- A. Apply a non-linear mapping to the result obtained after the weighted summation.
- B. Compute the weighted sum of the value vectors using the attention weights.
- C. Calculate the dot product similarity between the query and key vectors to obtain attention scores.
- D. Normalize the attention scores to obtain attention weights.
Correct Answer: B,C,D 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
In cases where the bright and dark areas of an image are too extreme, which of the following techniques can be used to improve the image?
- A. Inversion
- B. Gamma correction
- C. Grayscale stretching
- D. Grayscale compression
Correct Answer: B 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
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