Last Updated: Jul 30, 2026
No. of Questions: 175 Questions & Answers with Testing Engine
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Huawei H13-311-ENU certification exam is designed to validate the knowledge and skills of candidates in the field of Artificial Intelligence (AI). HCIA-AI (Huawei Certified ICT Associate-Artificial Intelligence) certification is an excellent opportunity for individuals interested in the fascinating and fast-growing field of AI. Huawei, being one of the leading technology companies in the world, has developed this certification to ensure that professionals have the necessary skills to implement AI technologies to real-world scenarios.
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The H13-311-ENU certification exam is part of the Huawei Certified ICT Associate-Artificial Intelligence (HCIA-AI) program. The program is designed for individuals who want to develop their knowledge and skills in AI, machine learning, deep learning, and other related fields. HCIA-AI (Huawei Certified ICT Associate-Artificial Intelligence) certification exam is a comprehensive test that covers a wide range of topics, including AI technologies, data processing, and machine learning algorithms.
| Section | Weight | Objectives |
|---|---|---|
| Huawei AI Solutions & Applications | 5% | - Full-stack all-scenario AI strategy - Edge/cloud AI deployment scenarios - Ascend chips, Atlas hardware, CANN |
| Deep Learning Overview | 25% | - CNN, RNN/LSTM, Transformer basics - Activation, loss functions, optimizers - Neural network structure and backpropagation |
| AI Overview | 15% | - Definition, history and development trends of AI - Main technical branches: ML, DL, computer vision, NLP - Typical industry applications and AI ethics |
| AI Development Frameworks | 20% | - TensorFlow/PyTorch basics - MindSpore framework fundamentals and operations - Huawei Cloud ModelArts, Ascend AI ecosystem |
| Machine Learning Overview | 20% | - Model training, evaluation, overfitting, underfitting - Supervised, unsupervised, reinforcement learning - Common algorithms: regression, decision tree, SVM, clustering |
| Mathematics and Python Basics | 15% | - Linear algebra, probability, statistics, calculus fundamentals - Python syntax, data structures, libraries: NumPy, Pandas, Matplotlib |
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