Huawei HCIP-AI-EI Developer V2.5 : H13-321_V2.5 Exam

  • Exam Code: H13-321_V2.5
  • Exam Name: HCIP-AI-EI Developer V2.5
  • Updated: Jul 24, 2026
  • Q & A: 62 Questions and Answers

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About Huawei HCIP-AI-EI Developer V2.5 : H13-321_V2.5 Exam Questions

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Huawei H13-321_V2.5 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Theoretical Knowledge and Applications of Natural Language Processing10%- Language model and semantic understanding
- Practical application
- Machine translation, text generation and other technologies
- Text processing and representation
Topic 2: Speech Processing Lab Guide12%- Speech data processing practice
- Application deployment and verification
- Speech model building and tuning
Topic 3: Neural Network Basics4%- Common neural network structures
- Training and optimization methods
- Basic concepts of neural networks
Topic 4: Overview of ModelArts4%- Core functions and service modules
- Basic operation process
- ModelArts positioning and architecture
Topic 5: Theoretical Knowledge and Applications of Image Processing26%- Feature extraction and representation
- Image preprocessing technology
- Typical application scenarios
- Image classification, detection and segmentation
Topic 6: Theoretical Knowledge and Applications of Speech Processing10%- Application cases
- Speech recognition and synthesis
- Speech feature extraction
- Speech signal processing foundation
Topic 7: Image Processing Lab Guide12%- Performance optimization and testing
- Development environment setup
- Image processing model development and deployment
Topic 8: Overview of Huawei's AI Development Strategy and Full-Stack, All-Scenario AI Portfolio2%- Huawei AI development layout
- Full-stack AI technology system
- All-scenario AI solutions
Topic 9: Natural Language Processing Lab Guide10%- Text preprocessing and feature engineering
- End-to-end application development
- NLP model training and evaluation

Huawei HCIP-AI-EI Developer V2.5 Sample Questions:

1. Which of the following statements about the functions of the encoder and decoder is true?

A) The encoder converts variable-length input sequences into fixed-length context vectors, encoding the information of the input sequences in the context vectors.
B) The encoder converts context vectors into variable-length output sequences.
C) The output lengths of the encoder and decoder are the same.
D) The decoder converts variable-length input sequences into fixed-length context vectors, encoding the information of the input sequences in the context vectors.


2. 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.)


3. 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


4. The development of large models should comply with ethical principles to ensure the legal, fair, and transparent use of data.

A) FALSE
B) TRUE


5. Which of the following are object detection algorithms?

A) YOLO
B) SSD
C) R-CNN
D) Faster-R-CNN


Solutions:

Question # 1
Answer: A
Question # 2
Answer: Only visible for members
Question # 3
Answer: B
Question # 4
Answer: B
Question # 5
Answer: A,B,C,D

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