PDF Version DemoHuawei H13-321_V2.5 Exam Overview:
| Certification Vendor: | Huawei |
| Exam Name: | Huawei HCIP-AI-EI Developer V2.5 Certification Exam |
| Exam Number: | H13-321_V2.5 |
| Available Languages: | English, Simplified Chinese |
| Real Exam Qty: | 60-70 |
| Exam Duration: | 90 minutes |
| Related Certifications: | HCIA-AI HCIP-AI-EI Developer |
| Exam Price: | USD 200 (varies by region) |
| Passing Score: | 600/1000 |
| Exam Format: | Single choice, Multiple choice, True/False, Drag and drop |
| Certificate Validity Period: | 3 years |
| Recommended Training: | Huawei HCIP-AI-EI Developer Training Huawei Cloud Academy AI Courses |
| Exam Registration: | Huawei Certification Portal Huawei Talent |
| Sample Questions: | Huawei H13-321_V2.5 Sample Questions |
| Exam Way: | Online proctored exam or authorized test center |
| Pre Condition: | Basic knowledge of AI, machine learning, and programming (Python recommended). HCIA-AI or equivalent knowledge is recommended. |
| Official Syllabus URL: | https://certification.huawei.com |
Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Machine Learning | - Unsupervised Learning
|
| Data Processing | - Data Labeling and Preparation - Data Collection and Cleaning - Feature Engineering |
| AI Fundamentals | - Common AI Use Cases in Industry - Introduction to Artificial Intelligence - AI Development Lifecycle |
| AI Application Development (EI) | - AI Service Integration - Building AI Applications - Enterprise Intelligence (EI) Concepts |
| Deep Learning | - Model Training and Optimization - Neural Network Fundamentals - CNN and RNN Architectures |
| Model Development with Huawei ModelArts | - Training Models on ModelArts - ModelArts Platform Overview - AutoML Capabilities |
| Model Deployment and Operations | - Monitoring and Maintenance - Inference Services - Model Deployment Strategies |
| Huawei AI Ecosystem Tools | - AI Development Toolchain - Huawei Cloud AI Services - MindSpore Framework Basics |
Huawei HCIP-AI-EI Developer V2.5 Sample Questions:
1. How many parameters need to be learned when a 3 × 3 convolution kernel is used to perform the convolution operation on two three-channel color images?
A) 9
B) 10
C) 55
D) 28
2. What are the advantages of deep learning-based speech recognition algorithms?
A) Automated feature extraction
B) No data training
C) Forced alignment of annotated data
D) End-to-end task processing
3. Vision transformer (ViT) performs well in image classification tasks. Which of the following is the main advantage of ViT?
A) It can process high-resolution images to enhance classification accuracy.
B) It achieves fast convergence without using pre-trained models.
C) It can handle small datasets with minimal labeling required.
D) The self-attention mechanism is used to capture global features of images, improving classification accuracy.
4. Which of the following statements about the multi-head attention mechanism of the Transformer are true?
A) Each header's query, key, and value undergo a shared linear transformation to obtain them.
B) The multi-head attention mechanism captures information about different subspaces within a sequence.
C) The concatenated output is fed directly into the multi-headed attention mechanism.
D) The dimension for each header is calculated by dividing the original embedded dimension by the number of headers before concatenation.
5. Huawei Cloud ModelArts is a one-stop AI development platform that supports multiple AI scenarios. Which of the following scenarios are supported by ModelArts?
A) Object detection
B) Speech recognition
C) Image classification
D) Video analytics
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: A,D | Question # 3 Answer: D | Question # 4 Answer: B,D | Question # 5 Answer: A,B,C,D |
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