Hi, I'm Badugu Jyothika
Computer Science Engineering Student
A undergraduate engineering student at Sridevi Women's Engineering College , Hyderabad.
Contact meAbout Me
My introduction
Hi, I'm a CSE undergraduate with a deep passion for technology and an ever-curious mindset. I thrive in dynamic environments that challenge me to grow and innovate. With a self-motivated and can-do attitude, I'm always eager to learn new technologies that inspire me and help me become better—both personally and professionally. I enjoy building projects that solve real problems and push my technical boundaries. Whether it's web development, data analytics, or exploring machine learning, I'm always up for diving into something exciting. Currently seeking opportunities that allow me to contribute meaningfully while continuing to enhance my skills in a collaborative and forward-thinking team.
CGPA
experience
Skills
My technical levelProgramming Languages
Java
HTML/CSS
JavaScript
Python
CSE Constructs
DBMS
DS & Algorithms
OOP
OS
Technologies
Git
MySQL
NodeJs
Qualification
My personal journeySSC
Srisai vidhyanikeythan High SchoolClass 12th
Sri Chaithanya Pre University CollegeCollege
Sridevi Women's Engineering College, HyderabadProjects
Most recent work
TO-DO-LIST
A simple to-do list web app to help you stay organized. Add, delete, and manage tasks efficiently. Built using HTML, CSS, and JavaScript.
GitHub Repository
AGE CALCULATOR
A simple and interactive age calculator that lets users calculate their age based on the date of birth input. Built with HTML, CSS, and JavaScript.
GitHub Repository
Basic Calculator
A basic calculator built using HTML, CSS, and JavaScript that performs fundamental arithmetic operations like addition, subtraction, multiplication, and division.
GitHub Repository
E-commerce Website
A front-end E-commerce website with product pages, navigation, and cart interface. Designed with modern UI principles using HTML, CSS, and JavaScript.
GitHub Repository
EV_vechiles price prediction
A machine learning project to predict electric vehicle prices based on key features like brand, range, and battery capacity. Built using Python, Pandas, and Scikit-learn Implemented models: Random Forest, and Gradient Boosting Performed data cleaning, EDA, and model evaluation (R², RMSE) Modular code, ready for deployment
GitHub Repository