What you will learn

• Explain key concepts, tools, and roles involved in machine learning, including supervised and unsupervised learning techniques.

• Apply core machine learning algorithms such as regression, classification, clustering, and dimensionality reduction using Python and scikit-learn.

• Evaluate model performance using appropriate metrics, validation strategies, and optimization techniques.

• Build and assess end-to-end machine learning solutions on real-world datasets through hands-on labs, projects, and practical evaluations.