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Updated in [July 27th, 2023]
This course provides learners with the skills and knowledge necessary to clean and preprocess data in Python for Machine Learning. It covers a range of data cleaning techniques, such as imputing missing values, feature scaling, fixing data types issues, detecting and dealing with incorrect values, using the Apply Lambda method for advanced cleaning functions, grouping the dataset by a particular column, detecting and removing outliers, and cleaning and preprocessing textual data for NLP. Through lectures, quizzes, and Jupyter notebooks, learners will gain the skills to effectively deal with real world raw data.
Course Syllabus
Introduction and Setup
Detecting Data Quality issues
Data Cleaning and Preprocessing
Data Cleaning and Preprocessing for NLP