Machine Learning : From Basics to Projects

This hands-on course introduces you to the fundamentals of Machine Learning (ML) through 8 structured modules. You’ll start with the basics of ML and data preprocessing, then dive into supervised learning (regression & classification), unsupervised learning (clustering & dimensionality reduction), and model selection techniques. Practical learning is emphasized with multiple guided projects, such as: - Data Cleaning & Preprocessing (Student Score Dataset) - Predicting House Prices with Linear Regression - Pass/Fail Prediction using Logistic Regression - Customer Segmentation with K-Means Clustering - Handwritten Digit Recognition using a simple Neural Network The course culminates in a Capstone Project, where you’ll build and deploy a complete ML solution such as a Movie Recommendation System or Employee Attrition Predictor. By the end, you’ll gain strong foundational skills in data preprocessing, regression, classification, clustering, model evaluation, and neural networks, preparing you for careers in Machine Learning, Data Science, and AI.