Learn methods for identifying and handling inconsistencies in your dataset, including missing values, outliers, and duplicates, to improve accuracy and integrity.
Understand how to normalize, standardize, and scale features for compatibility with analytical and machine learning models.
Discover how to merge datasets from different sources and format them into clean, analyzable structures.