Machine Learning Full Course with Projects (Beginners to Advanced Level)

About this path

This learning path takes you from the basics of machine learning to core algorithms like regression, classification, and ensemble methods. You'll start with concepts and setup, then move through data preparation and supervised learning techniques. Each video builds on the previous one, so follow the order for a smooth learning experience.

What you will learn

• Understand what machine learning is and its real-world applications
• Explain the machine learning lifecycle and key concepts like datasets, features, and labels
• Set up Python and Anaconda for machine learning
• Differentiate between supervised and unsupervised learning
• Apply data preprocessing techniques
• Implement and interpret regression models (linear, polynomial, logistic)
• Use classification algorithms like decision trees, random forest, naive Bayes, and SVM
• Evaluate models using confusion matrix and handle overfitting/underfitting

Who this is for

Beginners who want a structured free introduction before deeper practice.

Curriculum