Over a two-month period, contributed to the Intelligent-Advisor-Sem-4 repository by developing a scalable stock price prediction API and a user-facing dashboard. Leveraging Python, FastAPI, and React, implemented robust input validation, integrated machine learning models for stock forecasting, and established endpoints for stock data retrieval and prediction. Enhanced backend reliability through environment-based configuration, improved CORS handling, and database integration using SQLAlchemy. On the frontend, delivered a dashboard for historical data visualization and model performance metrics, enabling users to interact with predictions and export results. Addressed code quality by refining error handling and removing runtime noise, supporting maintainable and reliable operations.