Machine Learning with Scikit-learn: From Basics to Preprocessing

About this path

This learning path is based on the Scikit-learn Tutorial playlist by CodersArts. It is designed for beginners who want to get started with machine learning using Python. You will learn the core features of Scikit-learn, build regression and classification models, and understand key preprocessing techniques for handling missing data, categorical values, and feature scaling. Each video includes practical code examples to help you apply what you learn.

What you will learn

• Understand the basics of Scikit-learn and its role in machine learning
• Implement linear and multiple linear regression models
• Apply logistic regression for classification tasks
• Use K-Nearest Neighbors and decision tree algorithms
• Build random forest models and evaluate with confusion matrices
• Preprocess data using imputation, encoding, discretization, and scaling
• Use polynomial features and custom transformers

Who this is for

Beginners who want a structured free introduction before deeper practice.

Curriculum