WELCOME TO MY PORTFOLIO

I'm SUJITHA

I'm a FULL STACK DEVELOPER - FRONTEND AND BACKEND

ABOUT ME

CURRENTLY

I am a passionate Full Stack Developer in training. Currently learning how to build beautiful, responsive, and user-friendly web applications. As a fresher, I am eager to explore the world of web development and improve my skills by working on real-world projects.

My Goals

  • Build projects to practice and showcase my skills.
  • Learn modern frontend frameworks like React.
  • Improve my problem-solving skills through coding challenges.

EDUCATION

B.E - Computer Science and Engineering

I did my college Under Anna University Affiliated College in Madurai. Passed out in the year of 2024. I have get passed in First class with overall CGPA - 7.81




HSC & SSLC

I did my schooling Governement Girls Higher Secondary School in Sholavandan. Passed out in the year from 2018 to 2020.

INTERNSHIPS

Asp.NET
Intership in Web Development & Hosting using .NET in Futurik Technology at Madurai.



Aptitude Training
I was attended Aptitude Training in Naandi Foundation.



Employability skill training
I was attended Employability Skills Traning program in Naandi Foundation.

MY SKILLS

Technical Skills

HTML

95%

CSS

90%

Bootstrap

82%

JavaScript

58%

MySQL

78%

PROJECTS

PROJECT-1

Mini Java Compiler Using Lexical Analyser

The Mini Java Compiler is a simplified implementation of a Java compiler that utilizes a lexical analyzer to process Java source code. This project focuses on the initial phases of compilation, specifically lexical analysis, which involves tokenizing the source code into meaningful symbols that can be further processed in later stages like parsing and semantic analysis.

PROJECT-2

Early stage Prognostication of Autism Spectrum Disorder Using Machine Learning

Developed a machine learning model aimed at the early detection and prognostication of Autism Spectrum Disorder (ASD). The project involved collecting and preprocessing a diverse dataset, including behavioral, genetic, and demographic features associated with ASD. Utilized various machine learning algorithms, such as Random Forest, Support Vector Machines, and analyze the data and identify patterns indicative of ASD.

CONTACT