Data Cleaning Skill

Overview

Master data cleaning and preprocessing techniques essential for reliable analytics.

Topics Covered

• Missing value handling (imputation, deletion)
• Outlier detection and treatment
• Data type conversion and validation
• Duplicate identification and removal
• String cleaning and normalization

Learning Outcomes

• Clean messy datasets
• Handle missing data appropriately
• Detect and treat outliers
• Ensure data quality

Error Handling