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Huawei H13-321_V2.0 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Speech Processing Lab Guide12%- Speech application development on ModelArts
Topic 2: Overview of Huawei AI Development Strategy and Full-Stack, All-Scenario AI Portfolio2%
Topic 3: Image Processing Lab Guide12%- ModelArts-based image development
Topic 4: Theoretical Knowledge and Applications of Natural Language Processing10%- NLP core concepts
- Text processing and representation
- Common NLP tasks and applications
Topic 5: Natural Language Processing Lab Guide10%- NLP project practice on ModelArts
Topic 6: Theoretical Knowledge and Applications of Speech Processing10%- Speech recognition and synthesis
- Speech processing basics
- Acoustic and language models
Topic 7: Theoretical Knowledge and Applications of Image Processing26%- Computer vision overview
- Image preprocessing and feature extraction
- Convolutional neural networks
- Image recognition, detection and segmentation
Topic 8: Neural Network Basics4%- Network training and optimization
- Deep learning fundamentals
- Artificial neural network principles
Topic 9: Overview of ModelArts4%- Development and deployment workflow
- ModelArts platform architecture
Topic 10: ModelArts Platform Development Experiment10%

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

1. ModelArts is a one-stop AI development platform built around the AI development process. Users can customize and develop AI models based on ModelArts . ModelArts ' capabilities cover all aspects of AI development.

A) True
B) False


2. Which of the following options belongs to the preparation task before the third step of training the neural network (calculating the loss value between the predicted value and the target value through the loss function)? (Multiple choice)

A) Define the network structure and initialize network parameters
B) Model converges and training ends
C) Input data features and get predicted values through forward propagation
D) Update parameters by minimizing the loss value through gradient descent and back propagation algorithm


3. Which of the following options is not a method in the development of natural language processing?

A) Recursion-based methods
B) Statistical-based methods
C) Rule-based approach
D) Deep Learning-Based Methods


4. Which of the following belongs to the optimizer in gradient descent? (Multiple choice)

A) Adagrad (Adaptive Gradient Descent Optimizer)
B) momentum
C) Adam (improved version of the optimizer)
D) Adaboost (Ensemble learning idea)


5. Which of the following belongs to convolutional neural network? (Multiple choice)

A) VGG16
B) LSTM
C) RNN
D) Resnet


Solutions:

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

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