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Huawei H13-731_V3.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Preprocessing and Feature Engineering | 20% | - Handling missing values and outliers - Data cleaning, integration and transformation - Feature selection, extraction and dimensionality reduction |
| Data Mining Algorithms | 30% | - Classification and regression algorithms - Clustering and association rule mining - Anomaly detection and pattern recognition |
| Huawei Big Data Platform and Solutions | 10% | - Data mining and analysis tools on Huawei ecosystem - Solution deployment and performance optimization - FusionInsight architecture and components |
| Big Data and Data Mining Fundamentals | 20% | - Data mining concepts, processes and applications - Statistics and probability foundations - Big Data architecture and ecosystem |
| Machine Learning and Distributed Analytics | 20% | - Distributed computing frameworks (Spark, Hadoop) - Hyperparameter tuning and optimization - Model training, validation and evaluation |



