Introduction to Data Cleaning with Python

This course explores advanced Pandas functionalities for transforming data, handling categorical and text data, processing date-time values, and performing feature engineering for better analysis.

This course ensures data integrity, feature selection, anomaly detection, and validation for ML models. The goal is to remove noisy, inconsistent, or biased data before training.

This course focuses on automating the data cleaning process using Python. It covers pipeline creation, automation with functions, handling large datasets efficiently, and logging and debugging.

This course extends data cleaning techniques to handle text-based data in tabular datasets. It covers cleaning and processing text columns, dealing with mixed data types, extracting meaningful features from text, and preparing text data for machine learning.