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

  • Exam Code: H13-321_V2.5
  • Exam Name: HCIP-AI-EI Developer V2.5
  • Updated: Aug 06, 2026
  • Q&As: 62 Questions and Answers

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Huawei H13-321_V2.5 Exam Syllabus Topics:

SectionObjectives
Topic 1: Deep Learning- Neural Network Fundamentals
- Model Training and Optimization
- CNN and RNN Architectures
Topic 2: AI Application Development (EI)- AI Service Integration
- Enterprise Intelligence (EI) Concepts
- Building AI Applications
Topic 3: Huawei AI Ecosystem Tools- MindSpore Framework Basics
- AI Development Toolchain
- Huawei Cloud AI Services
Topic 4: Data Processing- Data Collection and Cleaning
- Data Labeling and Preparation
- Feature Engineering
Topic 5: Machine Learning- Supervised Learning
  • 1. Classification Algorithms
    • 2. Regression Algorithms
      - Unsupervised Learning
      • 1. Clustering Methods
        • 2. Dimensionality Reduction
          Topic 6: Model Deployment and Operations- Monitoring and Maintenance
          - Model Deployment Strategies
          - Inference Services
          Topic 7: Model Development with Huawei ModelArts- ModelArts Platform Overview
          - Training Models on ModelArts
          - AutoML Capabilities
          Topic 8: AI Fundamentals- Introduction to Artificial Intelligence
          - Common AI Use Cases in Industry
          - AI Development Lifecycle

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

          1. 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) TRUE
          B) FALSE


          2. The technologies underlying ModelArts support a wide range of heterogeneous compute resources, allowing you to flexibly use the resources that fit your needs.

          A) TRUE
          B) FALSE


          3. In the image recognition algorithm, the structure design of the convolutional layer has a great impact on its performance. Which of the following statements are true about the structure and mechanism of the convolutional layer? (Transposed convolution is not considered.)

          A) A stride in the convolutional layer can control the spatial resolution of the output feature map. A larger stride indicates a smaller output feature map and simpler calculation.
          B) In the convolutional layer, each neuron only collects some information. This effectively reduces the memory required.
          C) The convolutional layer slides over the input feature map using a convolution kernel of a fixed size to extract local features without explicitly defining their features.
          D) The convolutional layer uses parameter sharing so that features at different positions share the same group of parameters. This reduces the number of network parameters required but reduces the expression capabilities of models.


          4. Which of the following statements about the standard normal distribution are true?

          A) The variance is 0.
          B) The mean is 0.
          C) The variance is 1.
          D) The mean is 1.


          5. If a scanned document is not properly placed, and the text is tilted, it is difficult to recognize the characters in the document. Which of the following techniques can be used for correction in this case?

          A) Perspective transformation
          B) Affine transformation
          C) Grayscale transformation
          D) Rotational transformation


          Solutions:

          Question # 1
          Answer: A
          Question # 2
          Answer: A
          Question # 3
          Answer: A,B,C,D
          Question # 4
          Answer: B,C
          Question # 5
          Answer: B,D

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