

A driven Computer Science student with practical experience in Artificial Intelligence and Machine Learning, demonstrated by successfully designing and training a Convolutional Neural Network (CNN) for the early prediction and classification of heart disease, achieving 87% predictive accuracy using Python and deep learning frameworks like TensorFlow/Keras. This technical depth is complemented by proven problem-solving and rapid development skills, evidenced by securing 5th place nationally in the SAP Hackfest..
Machine Learning and Artificial Intelligence -
Project: CNN-Based Heart Disease Prediction
Python
Secured 5th Position in National Level Hackathon (SAP Hackfest)
Machine Learning And Artificial Intelligence
SAP Hackfest 2025 - A National Level Hackathon
Machine Learning And Artificial Intelligence
From Learner to Builder: Become an AI Agent Architect
Advanced Excel
Workshop on Game Development With GODOT
Data Science