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Huawei H13-321_V2.0-ENU exam : HCIP-AI-EI Developer V2.0
- Exam Code: H13-321_V2.0-ENU
- Exam Name: HCIP-AI-EI Developer V2.0
- Updated: Oct 04, 2026
- Q & A: 574 Questions and Answers
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Huawei H13-321_V2.0-ENU Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Natural Language Processing Theory and Applications | 10% | - BERT, GPT and pre-trained models - Word representation and embedding - Text classification, NER, machine translation - RNN, LSTM, GRU, Transformer architecture |
| Topic 2: Neural Network Basics | 4% | - Basic concepts of neural networks - Activation functions and regularization - Multilayer Perceptron (MLP) - Gradient descent and backpropagation |
| Topic 3: Image Processing Lab Guide | 12% | - ModelArts-based image classification - Object detection and segmentation practice - Ascend-based deployment |
| Topic 4: Speech Processing Lab Guide | 12% | - Huawei Cloud Speech Interaction Service - ModelArts speech application deployment - ASR and TTS service development |
| Topic 5: Speech Processing Theory and Applications | 10% | - Text-to-Speech (TTS) technology - Acoustic and language modeling - Speech signal characteristics and processing - Automatic Speech Recognition (ASR) |
| Topic 6: Image Processing Theory and Applications | 26% | - Image classification, object detection, segmentation - OCR and visual application development - Image processing fundamentals - Convolutional Neural Networks (CNN) |
| Topic 7: Huawei AI Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | - Full-stack and all-scenario AI technology layout - Huawei AI development strategy |
| Topic 8: Natural Language Processing Lab Guide | 10% | - ModelArts NLP model training and tuning - Application integration and deployment - Text classification and NER implementation |
| Topic 9: Overview of ModelArts | 4% | - ModelArts platform positioning and architecture - Data processing, training, deployment capabilities - Development environment and tool usage |
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
Question #1
What are the four elements of artificial intelligence? (Multiple choice)
- A. Algorithm
- B. Computing power
- C. Data
- D. Scenario
Correct Answer: A,B,C,D 🗳️
Question #2
Which of the following options are applications of natural language processing? (Multiple choice)
- A. Automatic Summarization
- B. Text Classification
- C. Public Opinion Analysis
- D. Question Answering System
Correct Answer: A,B,C,D 🗳️
Question #3
Which of the following layers does a convolutional neural network usually contain? (Multiple choice)
- A. Input layer
- B. Convolutional Layer
- C. Output layer
- D. Fully connected layer
Correct Answer: A,B,C,D 🗳️
Question #4
The back propagation algorithm can be programmed to calculate the gradient of the neural network weights, thereby completing the training of the neural network through gradient descent.
- A. False
- B. True
Correct Answer: B 🗳️
Question #5
Which of the following options is the algorithm used to estimate the parameters of a single Gaussian model?
- A. Maximum Likelihood Estimation
- B. EM algorithm
- C. Viterbi algorithm
- D. Forward-backward algorithm
Correct Answer: A 🗳️
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