Driven by a deep passion for understanding the physics behind the world, I completed my BSc and MSc in Physics. Through my studies, I found myself drawn to computational physics, where I honed my coding skills and developed a strong interest in the world of technology. During my academic journey, I undertook projects that required computational expertise, which reinforced my programming foundation.During my bachelor’s, I worked on "Development of a Monte Carlo program to simulate Mono-atomic Fluids" in Fortran90, which strengthened my coding abilities and understanding of Monte Carlo simulations. In my MSc, we worked on "Performance Assessment of Calibration X-ray source for ITER X-ray Crystal Spectrometer" using OASYS software. This project requires handling data, data visualization, data fitting, which was done in Python. These experiences in data handling and computational projects reinforced my technical foundation and broadened my problem-solving skills.Post-graduation, my enthusiasm for coding continued to grow, leading me to dive into the fields of Machine Learning (ML) and Data Science. I took time to intensively study these areas, gaining a solid foundation in the latest tools and techniques shaping the future of technology. I completed a certificate course in Machine Learning Specialization by Andrew Ng from Coursera (Stanford and DeepLearning.AI) and have also studied Exploratory Data Analysis, SQL, and Statistics form Campusx, and krish Naik (Youtube). Now, My future goal is to dive deeper into Deep Learning, Large Language Models (LLMs), and MLOps.Today, I am excited to be working at the intersection of physics, coding, and data, and I am eager to contribute to impactful projects in ML and Data Science that push the boundaries of innovation.