Prepare and pass exam with our Huawei H13-321_V2.5 training material, here you will achieve your dream easily With TrainingQuiz!
Updated: Aug 11, 2026
No. of Questions: 62 Questions & Answers with Testing Engine
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| 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 |
| Related Certifications: | HCIA-AI HCIP-AI-EI Developer |
| Exam Format: | Single choice, Multiple choice, True/False, Drag and drop |
| Passing Score: | 600/1000 |
| Certificate Validity Period: | 3 years |
| Real Exam Qty: | 60-70 |
| Exam Duration: | 90 minutes |
| Exam Price: | USD 200 (varies by region) |
| Recommended Training: | Huawei HCIP-AI-EI Developer Training Huawei Cloud Academy AI Courses |
| Exam Registration: | Huawei Talent Huawei Certification Portal |
| 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 |
| Section | Objectives |
|---|---|
| Topic 1: Model Development with Huawei ModelArts | - AutoML Capabilities - ModelArts Platform Overview - Training Models on ModelArts |
| Topic 2: Data Processing | - Data Collection and Cleaning - Data Labeling and Preparation - Feature Engineering |
| Topic 3: Deep Learning | - Neural Network Fundamentals - CNN and RNN Architectures - Model Training and Optimization |
| Topic 4: Model Deployment and Operations | - Model Deployment Strategies - Inference Services - Monitoring and Maintenance |
| Topic 5: Huawei AI Ecosystem Tools | - MindSpore Framework Basics - AI Development Toolchain - Huawei Cloud AI Services |
| Topic 6: Machine Learning | - Supervised Learning
|
| Topic 7: AI Application Development (EI) | - Enterprise Intelligence (EI) Concepts - Building AI Applications - AI Service Integration |
| Topic 8: AI Fundamentals | - AI Development Lifecycle - Introduction to Artificial Intelligence - Common AI Use Cases in Industry |
1. In 2017, the Google machine translation team proposed the Transformer in their paperAttention is All You Need. The Transformer consists of an encoder and a(n) --------. (Fill in the blank.)
2. Seq2Seq is a model that translates one sequence into another sequence, essentially consisting of two recurrent neural networks (RNNs), one is the Encoder, and the other is the ---------. (Fill in the blank.)
3. Mel-frequency cepstral coefficients (MFCCs) take into account human auditory characteristics by first mapping the linear spectrum to the Mel nonlinear spectrum based on auditory perception, and then converting it to the cepstral domain.
A) FALSE
B) TRUE
4. The deep neural network (DNN)-hidden Markov model (HMM) does not require the HMM-Gaussian mixture model (GMM) as an auxiliary.
A) FALSE
B) TRUE
5. Which of the following is not an algorithm for training word vectors?
A) BERT
B) FastText
C) Word2Vec
D) TextCNN
Solutions:
| Question # 1 Answer: Only visible for members | Question # 2 Answer: Only visible for members | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: D |
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