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Huawei H13-321_V2.0-ENU Exam Syllabus Topics:

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

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

1. Modelarts images cannot be labeled in batches.

A) True
B) False


2. What are the advantages of using deep neural network structure to process speech recognition? (Multiple choice)

A) No need for speech signal feature extraction (the answer is to be determined)
B) Can complete tasks end-to-end
C) No sample labeling required
D) Can process longer sequence signals


3. How does the learning rate change when using the AdaGrad algorithm?

A) Increase first and then decrease
B) Decrease first and then increase
C) Increase
D) Reduce


4. Which of the following is the highlights of Huawei's deep learning framework MindSpore?

A) All of the above
B) Through MindSpore 's own technological innovation and the collaborative optimization of MindSpore and Ascend processors, efficient running state is achieved and computing performance is greatly improved.
C) By implementing the Al algorithm as code, the development environment becomes more friendly, significantly reducing model development time and lowering the model development threshold.
D) Natively adapt to every scenario including terminal, edge and cloud, and can collaborate on demand, with flexible deployment.


5. Modelarts' image labeling processing is charged based on time.

A) True
B) False


Solutions:

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

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