Excel-Based Analytics Platform
Summary
Developed a secure Excel file dashboard with interactive chart generation, utilizing React.js, Node.js, MongoDB, Chart.js, and JWT.
Aspiring Full Stack Web Developer with strong proficiency in the MERN stack, specializing in building scalable, real-time web applications. Delivered production-level projects, including a chat app and a data analytics dashboard that reduced manual analysis time by 70% for 100+ users. Eager to leverage expertise in clean code and collaborative development to contribute to impactful software solutions.
Web Developer Intern
Remote, Uttar Pradesh, India
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Summary
Developed and deployed robust web solutions for client projects, leveraging the MERN stack in a remote, collaborative environment.
Highlights
Successfully contributed to the development and deployment of 2 real-world client projects, utilizing the MERN stack to meet specific business requirements.
Integrated over 10 REST APIs, enhancing application functionality and improving backend performance by 30% through optimized data handling.
Collaborated effectively within a 4-person development team, utilizing Git for version control and participating in code reviews to ensure high code quality and maintainability.
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MCA
Computer Applications
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BCA
Computer Applications
Awarded By
Educational/Program Authority
Recognized for exceptional project performance in Full Stack Web Development.
Issued By
AWS Academy
Issued By
Deloitte
Issued By
One Roadmap
JavaScript (ES6+), Python.
React.js, Node.js, Express.js, Socket.IO, OpenCV, TensorFlow, Streamlit, Chart.js, Axios.
HTML5, CSS3, RESTful APIs, JWT, WebSocket.
MongoDB, MySQL.
Git, GitHub, Postman, VS Code.
Summary
Developed a secure Excel file dashboard with interactive chart generation, utilizing React.js, Node.js, MongoDB, Chart.js, and JWT.
Summary
Engineered a real-time 1-to-1 chat application with JWT authentication and WebSocket support, built using MERN Stack, Socket.IO, and JWT.
Summary
Created a facial emotion recognition system with 91% accuracy in live emotion classification, featuring a Streamlit interface for webcam-based testing, leveraging Python, OpenCV, TensorFlow, and Streamlit.