The Education Technology Revolution

Classification & Hypothesis Testing - Massachusetts Institute of Technology and Great Learning

Objective: Built a predictive model for ExtraaLearn to identify high-potential leads likely to convert into paying customers, improving lead allocation and marketing focus.

Approach: Used Decision Tree and Random Forest classifiers to model lead conversion likelihood, with EDA and hyperparameter tuning to optimize predictions.

Skills and Tools: Python, Scikit-learn, Pandas, data preprocessing, feature engineering, model tuning, visualization with Matplotlib and Seaborn.