Data Preprocessing and Feature Engineering

Learn practical techniques to clean, transform, and engineer data for machine learning using Python. This course covers essential preprocessing steps, feature creation, and hands-on challenges to prepare data for modeling.

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12 chapters

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Codefinity advantages

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Outcomes

Learning outcomes

Modules

Testimonials

Recommendations

Codefinity advantages

FAQs

What you will learn

Understanding the importance of data preprocessing in machine learning
Cleaning and handling missing, duplicated, and inconsistent data
Encoding categorical variables and scaling numerical features
Applying transformations to fix skewed distributions

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12 assignments

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There are 3 modules in this course

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Introduction to SQL

Intermediate SQL

Pandas First Steps

Excel Formulas

Advanced Techniques in pandas

Ultimate NumPy

Introduction to Neural Networks

Relational Database and Normalization

ML Introduction with scikit-learn

Ultimate Visualization with Python

Databases in Python

Introduction to NLP

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100+ Top-Rated courses

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Your subscription also includes:

Introduction to SQL

Intermediate SQL

Pandas First Steps

Excel Formulas

Advanced Techniques in pandas

Ultimate NumPy

Introduction to Neural Networks

Relational Database and Normalization

ML Introduction with scikit-learn

Ultimate Visualization with Python

Databases in Python

Introduction to NLP

Introduction to SQL

Intermediate SQL

Pandas First Steps

Excel Formulas

Advanced Techniques in pandas

Ultimate NumPy

Introduction to Neural Networks

Relational Database and Normalization

ML Introduction with scikit-learn

Ultimate Visualization with Python

Databases in Python

Introduction to NLP

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