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Updated: Jul 30, 2026
No. of Questions: 62 Questions & Answers with Testing Engine
Download Limit: Unlimited
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H13-321_V2.5 Practice Q&A's
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Huawei H13-321_V2.5 Exam Overview:
| Certification Vendor: | Huawei |
| Exam Name: | HCIP-AI-EI Developer V2.5 |
| Exam Number: | H13-321_V2.5 |
| Available Languages: | English, Chinese |
| Exam Price: | USD 300 |
| Related Certifications: | HCIA-AI-EI Developer HCIE-AI-EI Developer |
| Passing Score: | 600/1000 |
| Real Exam Qty: | 60-70 |
| Exam Format: | Multiple Choice, True or False, Drag and Drop, Simulation |
| Certificate Validity Period: | 3 years |
| Exam Duration: | 90 minutes |
| Sample Questions: | Huawei H13-321_V2.5 Sample Questions |
| Exam Way: | Online/Offline Testing Center |
| Pre Condition: | Recommended: HCIA-AI-EI Developer certification or equivalent knowledge of deep learning and Huawei cloud services |
| Official Syllabus URL: | https://support.huawei.com/hedex/hdx.do?docid=DOC1000203314 |
Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deep Learning Fundamentals | 15% | - Neural Network Basics - CNN and RNN Architectures - Training and Fine-tuning - Optimization Algorithms |
| Topic 2: Natural Language Processing Application | 15% | - Language Model Fine-tuning - Named Entity Recognition - Text Preprocessing and Embedding - Text Classification Models |
| Topic 3: HiLens Platform Development | 20% | - Skill Development Framework - Real-time Inference Optimization - Multi-modal Data Processing - Edge Deployment Strategy |
| Topic 4: ModelArts Pro Development | 20% | - Model Deployment and Management - Inference Service Configuration - AutoML and Automatic Model Training - Hyperparameter Optimization |
| Topic 5: EI Model Development Fundamentals | 15% | - Model Development Process - Development Environment Setup - HiLens Framework and Skills - EI Service and Architecture |
| Topic 6: Image Recognition Application Development | 15% | - Object Detection Implementation - Image Classification Models - Transfer Learning with Pre-trained Models - Image Segmentation |
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) Model development framework
D) Demand for computing power
2. The attention mechanism in foundation model architectures allows the model to focus on specific parts of the input data. Which of the following steps are key components of a standard attention mechanism?
A) Compute the weighted sum of the value vectors using the attention weights.
B) Normalize the attention scores to obtain attention weights.
C) Apply a non-linear mapping to the result obtained after the weighted summation.
D) Calculate the dot product similarity between the query and key vectors to obtain attention scores.
3. The mAP evaluation metric in object detection combines accuracy and recall.
A) FALSE
B) TRUE
4. Which of the following are object detection algorithms?
A) Faster-R-CNN
B) YOLO
C) SSD
D) R-CNN
5. Which of the following ModelArts training parameters is used to customize hyperparameters?
A) Algorithm Type
B) Compute Nodes
C) Resource Pool
D) Hyperparameter
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: A,B,D | Question # 3 Answer: A | Question # 4 Answer: A,B,C,D | Question # 5 Answer: D |
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