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: Aug 25, 2026
  • Q&As: 574 Questions and Answers

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Huawei H13-321_V2.0 Exam Syllabus Topics:

SectionWeightObjectives
Neural Network Basics4%- Multilayer Perceptron (MLP)
- Gradient descent and backpropagation
- Basic concepts of neural networks
- Activation functions and regularization
Speech Processing Lab Guide12%- ModelArts speech application deployment
- Huawei Cloud Speech Interaction Service
- ASR and TTS service development
Speech Processing Theory and Applications10%- Text-to-Speech (TTS) technology
- Speech signal characteristics and processing
- Acoustic and language modeling
- Automatic Speech Recognition (ASR)
Natural Language Processing Lab Guide10%- Application integration and deployment
- ModelArts NLP model training and tuning
- Text classification and NER implementation
Image Processing Theory and Applications26%- Image processing fundamentals
- Convolutional Neural Networks (CNN)
- Image classification, object detection, segmentation
- OCR and visual application development
Image Processing Lab Guide12%- Ascend-based deployment
- ModelArts-based image classification
- Object detection and segmentation practice
Natural Language Processing Theory and Applications10%- Text classification, NER, machine translation
- Word representation and embedding
- BERT, GPT and pre-trained models
- RNN, LSTM, GRU, Transformer architecture
Huawei AI Strategy and Full-Stack, All-Scenario AI Portfolio2%- Full-stack and all-scenario AI technology layout
- Huawei AI development strategy
Overview of ModelArts4%- Development environment and tool usage
- ModelArts platform positioning and architecture
- Data processing, training, deployment capabilities

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

1. The v component of the HSV color space and the Y component of the YUV color space both represent the brightness of the image and can be separated as the result of grayscale conversion of the color image.

A) False
B) True


2. Language models can be used to solve problems such as predicting the next word based on context.

A) False
B) True


3. Which of the following is not a NLP language feature?

A) Contextual word features
B) Single word features
C) Text Features
D) Texture features


4. The chi-square test is derived from the chi-square distribution in statistics. Starting from the (class, term) correlation table, it considers the correlation between each class and each term, and measures the lack of independence between the two (features and categories). The smaller the chi-square, the smaller the independence and the greater the correlation.

A) False
B) True


5. The OTSU algorithm traverses possible thresholds and selects the maximum segmentation threshold between the foreground area and the background area () as the optimal threshold.

A) Between-class variance
B) Absolute difference
C) Cumulative difference of pixel values
D) Area difference


Solutions:

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

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