This Machine Learning Foundations course is designed to help beginners build a strong understanding of core machine learning concepts with a special focus on regression analysis. The course provides detailed explanations of regression techniques, making it ideal for learners who want a deeper understanding of predictive modeling and statistical learning.

Students begin with the fundamentals of machine learning, including how machine learning models work, data analysis concepts, and the role of regression in predictive systems. The course gradually moves from beginner-level concepts to intermediate and advanced regression topics.

Key subjects covered include simple linear regression, multiple linear regression (MLR), regression evaluation, model optimization, and advanced regression methods. Learners also gain practical experience through hands-on machine learning projects that apply regression techniques to real-world datasets.

The course focuses on both theory and implementation, helping students understand how regression algorithms make predictions and how to improve model performance. It also strengthens foundational machine learning knowledge required for advanced AI and data science learning paths.