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Last Updated: Sep 30, 2026
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Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Theoretical Knowledge and Applications of Natural Language Processing | 10% | - Machine translation, text generation and other technologies - Text processing and representation - Language model and semantic understanding - Practical application |
| Topic 2: Neural Network Basics | 4% | - Common neural network structures - Training and optimization methods - Basic concepts of neural networks |
| Topic 3: Image Processing Lab Guide | 12% | - Performance optimization and testing - Development environment setup - Image processing model development and deployment |
| Topic 4: Natural Language Processing Lab Guide | 10% | - Text preprocessing and feature engineering - End-to-end application development - NLP model training and evaluation |
| Topic 5: Theoretical Knowledge and Applications of Image Processing | 26% | - Image classification, detection and segmentation - Feature extraction and representation - Typical application scenarios - Image preprocessing technology |
| Topic 6: Overview of ModelArts | 4% | - Core functions and service modules - ModelArts positioning and architecture - Basic operation process |
| Topic 7: Theoretical Knowledge and Applications of Speech Processing | 10% | - Speech recognition and synthesis - Speech feature extraction - Speech signal processing foundation - Application cases |
| Topic 8: Speech Processing Lab Guide | 12% | - Application deployment and verification - Speech data processing practice - Speech model building and tuning |
| Topic 9: Overview of Huawei's AI Development Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | - Full-stack AI technology system - All-scenario AI solutions - Huawei AI development layout |
Huawei HCIP-AI-EI Developer V2.5 Sample Questions:
If OpenCV is used to read an image and save it to variable "img" during image preprocessing, (h, w) = img.
shape[:2] can be used to obtain the image size.
- A. FALSE
- B. TRUE
Correct Answer: B 🗳️
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In natural language processing tasks, word vector evaluation is an important aspect for measuring the performance of a word embedding model. Which of the following statements about word vector evaluation are true?
- A. Word vector evaluation can be performed through intrinsic evaluation. Common methods include word similarity tasks and word analogy tasks.
- B. The word analogy task evaluates the capability of word vectors in capturing semantic relationships between words, for example, by determining whether "king - man + woman = ?" is close to "queen".
- C. Extrinsic evaluation is the main method used for evaluating word vectors because it directly reflects the performance of word vectors in real-world application tasks.
- D. Word similarity tasks typically employ manually labeled datasets to evaluate word vectors, compute the cosine similarity between word vectors, and compare it with the manual labeling result.
Correct Answer: A,B,D 🗳️
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The U-Net uses an upsampling mechanism and has a fully-connected layer.
- A. FALSE
- B. TRUE
Correct Answer: A 🗳️
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The objective of -------- is to extract and classify named entities in a text into pre-defined classes such as names, organizations, locations, time expressions, monetary values, and percentages. (Enter the abbreviation.)
Reveal Solution Discussion 0Correct Answer:
NER
Explanation:
NER(Named Entity Recognition) is a core NLP task that involves locating and categorizing entities within text into predefined categories like persons, organizations, places, dates, monetary values, and percentages.
NER is widely used in information extraction, question answering, and knowledge graph construction.
Exact Extract from HCIP-AI EI Developer V2.5:
"NER identifies and classifies named entities in text into categories such as person names, organizations, locations, time expressions, and numeric values." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Sequence Labeling Tasks
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 compression
- D. Grayscale stretching
Correct Answer: B 🗳️
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