Data Science & Analytics
6,567 learners
Data Cleaning and Preprocessing Techniques
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.
Pandas
Python
5 lessons
24 practices
2 hours
Data Cleaning and Preprocessing
Course details
Understanding and Handling Missing Values in Datasets with Python
Applying Missing Values Handling to Clients' Personal Information Dataset
Replacing Mean with Median
Filling the Missing Values in the Clients Dataset
Addressing Missing Values in Client Data
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