Huawei HCIP-AI-EI Developer V2.0 : H13-321_V2.0

  • Exam Code: H13-321_V2.0
  • Exam Name: HCIP-AI-EI Developer V2.0
  • Updated: Sep 23, 2026     Q & A: 574 Questions and Answers

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Huawei H13-321_V2.0 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Speech Processing22%- Speech Processing Theory and Applications
- Speech Processing Lab Guide
Topic 2: AI Fundamentals and Neural Networks4%- Neural Network Basics
Topic 3: Natural Language Processing (NLP)20%- NLP Lab Guide
- NLP Theory and Applications
Topic 4: Computer Vision (Image Processing)26%- Image Processing Theory and Applications
  • 1. Object detection basics
    • 2. Image classification concepts
      - Image Processing Lab Guide
      Topic 5: Huawei AI Ecosystem and ModelArts16%- Huawei AI Strategy and Ecosystem Overview
      - ModelArts Lab Guide
      - ModelArts Platform Overview

      Huawei HCIP-AI-EI Developer V2.0 Sample Questions:

      Question #1

      Which of the following descriptions of the bimodal adaptive threshold segmentation method are correct? (Multiple choice)

      • A. Histogram bimodal method is an easy-to-understand adaptive threshold algorithm
      • B. If the image grayscale histogram is obviously bimodal, the grayscale value corresponding to the valley between the two peaks is selected as the threshold for image segmentation.
      • C. The bimodal method divides the image into foreground and background according to the grayscale characteristics of the image. The larger the inter-class variance between the foreground and the background, the greater the difference between the two parts that make up the image.
      • D. If the grayscale histogram of the image is very flat or has multiple peaks, the bimodal method cannot be used to obtain a suitable threshold.
      Reveal Solution  Discussion  0

      Correct Answer: A,B,C,D  🗳️

      Question #2

      What are the preset image classification models supported by ModelArts? (Multiple choice)

      • A. Faster_RCNN_ResNet_Y2_50O
      • B. Inception_v3
      • C. ResNet_v1_50
      • D. Faster_RCNN_ResNet_v1_50
      Reveal Solution  Discussion  0

      Correct Answer: B,C  🗳️

      Question #3

      The purpose of speech signal preprocessing () is to emphasize the high-frequency part of speech, remove the influence of lip radiation, and increase the high-frequency resolution of speech (please fill in Chinese)

      Reveal Solution  Discussion  0

      Correct Answer:

      Pre-emphasis

      Question #4

      Match the following functions with the corresponding service modules

      Reveal Solution  Discussion  0

      Correct Answer:

      Jupyter Notebook: Development Environment Data Management: Dataset Training Job: Training Management Model Conversion: Model Management

      Question #5

      Speech synthesis is also known as speech conversion.

      • A. False
      • B. True
      Reveal Solution  Discussion  0

      Correct Answer: B  🗳️

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