Embarking on this course allows you to deeply understand and apply data cleaning and preprocessing techniques. It systematically covers the concepts of data cleaning, handling missing values, normalization, binning, encoding, and more, aiming to equip you with practical skills for preparing data for analysis or machine learning tasks.
Overview
Syllabus
- Lesson 1: Understanding and Handling Missing Values in Datasets with Python
- Lesson 2: Handling Duplicates and Outliers in Datasets
- Lesson 3: Understanding and Implementing Data Normalization Techniques in Python
- Lesson 4: Categorical Data Encoding Techniques in Python: An Introduction to Label and One-Hot Encoding
- Lesson 5: Data Binning Techniques: An Introduction and Implementation with Python and Pandas
