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Huawei H13-321_V2.0-ENU Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Fundamentals and Neural Networks | 4% | - Neural Network Basics |
| Topic 2: Natural Language Processing (NLP) | 20% | - NLP Theory and Applications - NLP Lab Guide |
| Topic 3: Speech Processing | 22% | - Speech Processing Lab Guide - Speech Processing Theory and Applications |
| Topic 4: Computer Vision (Image Processing) | 26% | - Image Processing Lab Guide - Image Processing Theory and Applications
|
| Topic 5: Huawei AI Ecosystem and ModelArts | 16% | - ModelArts Platform Overview - ModelArts Lab Guide - Huawei AI Strategy and Ecosystem Overview |
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
1. Language model can be used to dynamically generate word vectors for each word.
A) False
B) True
2. What are the classifications of machine learning methods? (Multiple choice)
A) Self-supervised learning
B) Reinforcement Learning
C) Unsupervised Learning
D) Supervised Learning
E) Semi-supervised learning
3. word2vec uses cosine value to calculate similarity, and the distance range is between 0-1. The larger the value, the higher the correlation between the two words.
A) False
B) True
4. For a 32-level grayscale image, how many levels can be distinguished from the darkest to the brightest at each sampling point?
A) 64
B) 256
C) 128
D) 32
5. Image recognition tasks can be divided into three levels, from low to high according to the abstractness of the processing content?
A) Image analysis, image processing, image understanding
B) Image analysis, image understanding, image processing
C) Image processing, image analysis, image understanding
D) Image understanding, image analysis, image processing
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A,B,C,D,E | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: C |




