Skills for Today, Success for Tomorrow
This introductory course provides a practical foundation in Machine Learning, guiding learners from core concepts to hands-on implementation. Students begin by understanding what machine learning is, its types, and real-world applications across industries. The course then walks through the complete ML workflow—from data preparation to model training and evaluation—using Scikit-learn. Learners build and evaluate regression and classification models, explore performance metrics, and understand common challenges such as overfitting and underfitting. The course also introduces unsupervised learning through K-Means clustering and essential preprocessing techniques like feature scaling. It concludes with a simple end-to-end machine learning project, enabling learners to apply their skills in a real-world scenario with confidence.
