Fundamentals of Machine Learning

Catalog description

This course provides an introduction to fundamental concepts in machine learning, including both supervised and unsupervised learning techniques. Students will engage in hands-on projects where they will apply machine learning models to real-world datasets using Python and popular libraries. The curriculum covers various algorithms, such as decision trees, support vector machines, and clustering methods. Additionally, students will learn about model evaluation, overfitting, and feature selection.