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  • Total Questions: 574
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Huawei H13-321_V2.0-ENU Exam Syllabus Topics:

SectionObjectives
Topic 1: Natural Language Processing Labs- Practical Development
  • 1. NLP Model Applications
  • 2. Text Analysis Experiments
Topic 2: Speech Processing Labs- Practical Development
  • 1. Speech AI Applications
  • 2. Speech Recognition Experiments
Topic 3: Neural Network Basics- Neural Network Fundamentals
  • 1. Deep Learning Basics
  • 2. Common Neural Network Models
  • 3. Artificial Neural Networks
Topic 4: Speech Processing Theory and Applications- Speech AI Technologies
  • 1. Speech Processing Scenarios
  • 2. Speech Recognition
  • 3. Speech Synthesis
Topic 5: Image Processing Labs- Practical Development
  • 1. Image Processing Experiments
  • 2. Computer Vision Implementation
Topic 6: Natural Language Processing Theory and Applications- NLP Fundamentals
  • 1. Text Processing
  • 2. NLP Application Development
  • 3. Language Understanding
Topic 7: Huawei AI Development Strategy and AI Portfolio- Huawei AI Ecosystem
  • 1. Full-Stack AI Strategy
  • 2. All-Scenario AI Architecture
  • 3. Huawei Cloud EI Services
Topic 8: Image Processing Theory and Applications- Computer Vision Fundamentals
  • 1. Image Recognition Applications
  • 2. Image Classification
  • 3. Object Detection
Topic 9: ModelArts Platform Overview- AI Development Platform
  • 1. Model Deployment
  • 2. AI Workflow Management
  • 3. Model Training

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

1. A single perceptron can solve the XOR problem.

A) True
B) False


2. In the NNLM model, what is the activation function used in the network output layer?

A) Sigmoid
B) Tanh
C) ReLU
D) Softmax


3. The output of most optical sensors is a continuous signal. The computer can only perform digital image processing after the continuous signal is converted into a discrete signal.

A) True
B) False


4. How difficult is speech recognition?

A) All of the above
B) Scenarios
C) Geographical factors
D) Personal characteristics


5. 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)


Solutions:

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

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