Mohamed Sheik Yousuf N

Full Stack Development - Intern

Sivaganga, IndiaSoftware Development
2roles
24skills
3education
3credentials

About

Recently completed a Computer Science degree from Fatima Michael College of Engineering and Technology, with strong skills in full-stack web development, specializing in Python-based back-end technologies such as Django and Flask. Experienced in building responsive front-end interfaces using HTML, CSS, JavaScript, and React. Passionate about creating user-friendly web applications and solving real-world problems. Eager to contribute to dynamic development teams and grow as a software engineer.

Experience

Full Stack Development - Intern

PanTech IT

12/2025 – 01/2026 · Madurai

• Designing and developing responsive web applications. • Implementing authentication and database integration. • Testing and debugging for smooth functionality.

Java Development - Intern

PanTech IT

06/2025 – 07/2025 · Madurai

• Developed and maintained Java-based applications using object-oriented programming principles, improving code efficiency and readability. • Worked with core Java concepts such as multithreading, collections, and exception handling to build robust backend logic. • Integrated Java applications with MySQL databases.

Education

Fatima Michael College of Engineering and Technology

BE, Computer Science Engineering

11/2022 – 06/2026

CGPA: 7.61/10

AL-HUDHA ISLAMIC INTERNATIONAL MATRICULATION HR.SEC SCHOOL

High School

06/2019 – 05/2022

HSC: 79.6%, SSLC: 79.6%

Al-Hudha Islamic International Matriculation Higher Secondary School

High School

06/2019 – 05/2022

HSC: 79.6%; SSLC: 79.6%

Skills

HTMLCSS(Bootstrap)JavaScript(JQuery)Python (Django)MySQLCSSBootstrapJavaScriptjQueryPythonDjangoFlaskReactJavaMachine LearningObject-Oriented ProgrammingMultithreadingCollectionsException HandlingAuthenticationDatabase IntegrationResponsive Web DevelopmentAPI DevelopmentTesting and Debugging

Projects

Phishing Website Detection

Developed and trained a Machine Learning model in Python to classify websites as phishing or legitimate based on URL and webpage features, ensuring high detection accuracy. Built a Java-based backend to handle API requests, process user-submitted URLs, and communicate with the ML model for seamless prediction results.