Topics Covered: AI vs ML vs Deep Learning ,Types of Machine Learning, ML Workflow, Python Environment Setup

Practical Activity: Install Python, Jupyter Notebook & Google Colab, Build your first Machine Learning program

Topics Covered: Data Collection, Data Types, Missing Value Handling, Encoding Techniques, Feature Scaling

Practical Activity: Titanic Dataset Preprocessing, Iris Dataset Cleaning

Topics Covered: Descriptive Statistics, Correlation Analysis, Data Visualization, Feature Selection

Practical Activity: Complete EDA using Pandas & Matplotlib

Topics Covered: Linear Regression, Multiple Regression, Polynomial Regression, Ridge Regression, Lasso Regression

Practical Activity: House Price Prediction, Salary Prediction Model

Topics Covered: Logistic Regression, K-Nearest Neighbors, Decision Tree, Random Forest, Naïve Bayes, Support Vector Machine, Evaluation Metrics

Practical Activity: Heart Disease Prediction, Diabetes Classification

Topics Covered: Overfitting & Underfitting, Cross Validation, Grid Search, Random Search, ML Pipelines

Practical Activity: Hyperparameter Tuning for Random Forest

Topics Covered: End-to-End ML Pipeline, Model Serialization, Streamlit Deployment, Explainable AI, AI Ethics

Practical Activity: Deploy a Complete Machine Learning Web Application