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Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Overview of ModelArts | 4% | - Core functions and service modules - ModelArts positioning and architecture - Basic operation process |
| Overview of Huawei's AI Development Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | - Full-stack AI technology system - All-scenario AI solutions - Huawei AI development layout |
| Theoretical Knowledge and Applications of Natural Language Processing | 10% | - Language model and semantic understanding - Text processing and representation - Machine translation, text generation and other technologies - Practical application |
| Neural Network Basics | 4% | - Basic concepts of neural networks - Training and optimization methods - Common neural network structures |
| Theoretical Knowledge and Applications of Image Processing | 26% | - Image classification, detection and segmentation - Image preprocessing technology - Typical application scenarios - Feature extraction and representation |
| Speech Processing Lab Guide | 12% | - Application deployment and verification - Speech model building and tuning - Speech data processing practice |
| Image Processing Lab Guide | 12% | - Performance optimization and testing - Development environment setup - Image processing model development and deployment |
| Natural Language Processing Lab Guide | 10% | - Text preprocessing and feature engineering - End-to-end application development - NLP model training and evaluation |
| Theoretical Knowledge and Applications of Speech Processing | 10% | - Speech recognition and synthesis - Speech signal processing foundation - Speech feature extraction - Application cases |
Huawei HCIP-AI-EI Developer V2.5 Sample Questions:
1. John wants to deploy a large model locally to implement the Q&A assistant function for his company. Which of the following factors is unnecessary for John to consider?
A) Output delay
B) Model security
C) Demand for computing power
D) Model development framework
2. What are the advantages of deep learning-based speech recognition algorithms?
A) Automated feature extraction
B) Forced alignment of annotated data
C) End-to-end task processing
D) No data training
3. Which of the following statements about the levels of natural language understanding are true?
A) Syntactic analysis is to find out the meaning of words, structural meaning, their combined meaning, so as to determine the true meaning or concept expressed by a language.
B) Pragmatic analysis is to study the influence of the language's external environment on the language users.
C) Speech analysis involves distinguishing independent phonemes from a speech stream based on phoneme rules, and then identifying syllables and their lexemes or words according to the phoneme form rules.
D) Semantic analysis is to analyze the structure of sentences and phrases to find out the relationship between words and phrases, as well as their functions in sentences.
E) Lexical analysis is to find the lexemes of a word and obtain linguistic information from them.
4. Overfitting is a condition where a model is overly simple and excessive generalization errors occur.
A) TRUE
B) FALSE
5. In the deep neural network (DNN)-hidden Markov model (HMM), the DNN is mainly used for feature processing, while the HMM is mainly used for sequence modeling.
A) TRUE
B) FALSE
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A,C | Question # 3 Answer: B,C,E | Question # 4 Answer: B | Question # 5 Answer: A |
