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Quanta is a revolutionary platform designed to elevate the interview process by integrating AI brilliance. This personalized interviewing website offers a unique experience by leveraging artificial intelligence to conduct interviews in three distinct sections: coding, DSA, and behavioral rounds.

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Quanta

Quanta is an innovative interview platform that leverages the power of generative AI to revolutionize the way individuals prepare for interviews across various categories. Whether you're seeking to ace a job interview, excel in academic admissions, or simply improve your communication skills, Quanta offers a personalized and immersive experience. Users can simulate interviews in their chosen field, receive real-time feedback, and gain valuable insights into their performance, all while harnessing the capabilities of cutting-edge AI technology. With Quanta, we're not just redefining interview preparation; we're empowering individuals to confidently pursue their goals with tailored, data-driven guidance.

Table of Contents

Features

  • Categorywise interview
  • detail feedback on user response at the end
  • Used Avatar to built interview environment
  • user friendly UI/UX design

Tech Stack

  • Front-end:

    • React.js
    • TypeScript
    • TailwindCSS
  • Back-end:

    • Java
    • Express.js
    • Node.js

Project Links

Front-end:

Back-end:

Screenshot

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Installation

To set up the project locally, follow these steps:

  1. Clone the repository:
git clone https://github.com/Hasims2001/quanta.git
cd frontend

run command in terminal

npm install

run project

npm start

Project Team

Feel free to explore the project using the provided links and discover the generative ai based interview sessions!

About

Quanta is a revolutionary platform designed to elevate the interview process by integrating AI brilliance. This personalized interviewing website offers a unique experience by leveraging artificial intelligence to conduct interviews in three distinct sections: coding, DSA, and behavioral rounds.

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Languages

  • TypeScript 43.8%
  • JavaScript 29.2%
  • Java 19.9%
  • HTML 4.8%
  • CSS 2.3%