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Huawei H13-311-ENU Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Development Frameworks | 20% | - Huawei Cloud ModelArts, Ascend AI ecosystem - MindSpore framework fundamentals and operations - TensorFlow/PyTorch basics |
| Topic 2: Mathematics and Python Basics | 15% | - Python syntax, data structures, libraries: NumPy, Pandas, Matplotlib - Linear algebra, probability, statistics, calculus fundamentals |
| Topic 3: Machine Learning Overview | 20% | - Model training, evaluation, overfitting, underfitting - Supervised, unsupervised, reinforcement learning - Common algorithms: regression, decision tree, SVM, clustering |
| Topic 4: Huawei AI Solutions & Applications | 5% | - Ascend chips, Atlas hardware, CANN - Edge/cloud AI deployment scenarios - Full-stack all-scenario AI strategy |
| Topic 5: AI Overview | 15% | - Typical industry applications and AI ethics - Definition, history and development trends of AI - Main technical branches: ML, DL, computer vision, NLP |
| Topic 6: Deep Learning Overview | 25% | - Neural network structure and backpropagation - Activation, loss functions, optimizers - CNN, RNN/LSTM, Transformer basics |
