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

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

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

Question 1

Natural language processing can be defined as a discipline that studies language problems in human-to-human communication and human-to-computer communication. Natural language processing requires the development of models that represent language ability and language application, the establishment of a computational framework to implement such language models, the proposal of corresponding methods to continuously improve such language models, the design of various practical systems based on such language models, and the discussion of the evaluation techniques of these practical systems.

A. False
B. True

Question 2

Which of the following is the correct solution process for maximum likelihood estimation?
1. Log-likelihood function
2. Probability density function
3. Likelihood function
4. Derivative and set the equation to 0
5. Solve equations

A. 4-1-3-2-5
B. 2-1-3-4-5
C. 2-3-1-4-5
D. 1-3-4-2-5

Question 3

After developers have trained models on ModelArts, they can share them on the AI market to monetize them. They can also use models trained by other developers to quickly integrate them into their own applications and reduce duplication of work.

A. False
B. True

Question 4

In the Genism package, when the word2vec parameter sg=1, it means that the CBOW algorithm is selected.

A. False
B. True

Question 5

ModelArts model conversion function can be used to convert and quantize Tensorflow models into tensorRT format. The converted model can be deployed and run on Nvidia p4 CPU.

A. False
B. True

Solutions:

Question 1
Answer: B

Question 2
Answer: C

Question 3
Answer: B

Question 4
Answer: A

Question 5
Answer: B