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Huawei H13-321_V2.0-ENU Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Natural Language Processing Lab Guide | 10% | - NLP project practice on ModelArts |
| Image Processing Lab Guide | 12% | - ModelArts-based image development |
| Overview of Huawei AI Development Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | |
| Speech Processing Lab Guide | 12% | - Speech application development on ModelArts |
| Overview of ModelArts | 4% | - ModelArts platform architecture - Development and deployment workflow |
| Theoretical Knowledge and Applications of Image Processing | 26% | - Image preprocessing and feature extraction - Convolutional neural networks - Computer vision overview - Image recognition, detection and segmentation |
| ModelArts Platform Development Experiment | 10% | |
| Neural Network Basics | 4% | - Network training and optimization - Artificial neural network principles - Deep learning fundamentals |
| Theoretical Knowledge and Applications of Speech Processing | 10% | - Acoustic and language models - Speech recognition and synthesis - Speech processing basics |
| Theoretical Knowledge and Applications of Natural Language Processing | 10% | - Text processing and representation - NLP core concepts - Common NLP tasks and applications |
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
1. Which of the following scenarios will use target tracking technology? (Multiple choice)
A) Text recognition (OCR)
B) Autonomous driving
C) Scene Monitoring
D) Intelligent Transportation
2. Use two 3x3 convolution kernels to convolve a three-channel color image. How many channels does the resulting feature map have?
A) 3
B) 1
C) 4
D) 2
3. Which of the following are the advantages of MindSpore? (Multiple choice)
A) Support GPU, CPU and other processors
B) Natively adapts to every scenario including terminal, edge and cloud, and can collaborate on demand, with flexible deployment
C) Through MindSpore 's own technological innovation and the collaborative optimization of MindSpore and Ascend processors, the efficiency of the running state is achieved and the computing performance is greatly improved.
D) By implementing the Al algorithm as code, the development environment becomes more friendly, significantly reducing model development time and lowering the model development threshold.
4. What is the unique gate structure of GRU?
A) Forget Gate
B) Input Gate
C) Output Gate
D) Update Gate
5. Machine translation refers to the use of deep learning models to translate English into Chinese characters.
A) True
B) False
Solutions:
| Question # 1 Answer: B,C,D | Question # 2 Answer: D | Question # 3 Answer: A,B,C,D | Question # 4 Answer: D | Question # 5 Answer: B |
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