Data Preparation focuses on collecting, cleaning, transforming, and organizing raw data for analysis and machine learning applications. It enables organizations to improve data quality and ensure consistency across datasets before processing or modeling. This training explains core concepts such as data cleansing, handling missing values, normalization, data transformation, and feature engineering. It also covers data integration, formatting, validation techniques, and preprocessing workflows for analytics and AI systems. You will learn how enterprises prepare structured and unstructured data for reporting, visualization, and predictive modeling. The course also highlights best practices for building reliable, accurate, and efficient data preparation pipelines.
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