Student Grade Prediction Models (Python, Tableau):
Developed regression models in Python using scikit-learn to predict students' final math grades from demographic, behavioral, and academic features. Preprocessed data using StandardScaler, MinMaxScaler, and one-hot encoding within pipelines. Trained and evaluated Linear Regression, Lasso, and Ridge models using cross-validation, R², and RMSE. Created complementary Tableau dashboards to visualize grade distributions, feature importance, and model performance for stakeholder presentation.
Relational SQL Queries for Banking & University Data (PostgreSQL, pgAdmin):
Used SQL in PostgreSQL/pgAdmin to write advanced queries with JOINs, subqueries, and SET operators across Banking and University databases; extracted insights into customer behavior, academic metrics, and account relationships using robust, reusable logic.