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AI-powered self-interview preparation platform. This platform will use the magic of AI and language processing to simulate real interview scenarios. It will give users feedback on their responses and provide helpful resources and suggestions to enhance their interview skills.

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AI-Powered Interview Preparation Platform

Welcome to the AI-Powered Interview Preparation Platform! This platform aims to help students practice for interviews effectively by simulating realistic interview scenarios using the power of AI and language processing. It provides personalized feedback, performance analytics, and a user-friendly interface to enhance interview skills and boost confidence.

Key Features

Interview Simulator:-

Our platform allows users to practice for different types of interviews, such as MERN, Node, or Java, by engaging in realistic conversations with an AI interviewer. The AI will dynamically generate relevant questions based on the chosen interview type and adapt its tone and style to create a lifelike interview experience.

Personalized Feedback:-

After each interview simulation, the AI will analyze the student's responses and provide constructive feedback. This feedback will evaluate the content, delivery, and overall performance of the student's answers. It will identify strengths and suggest areas for improvement, including communication skills, technical knowledge, and problem-solving abilities.

Performance Analytics:-

The platform tracks users' progress over time, presenting them with valuable insights into their interview preparation journey. Users can view success rates in different types of interviews, identify strengths and weaknesses, and monitor their improvement across multiple practice sessions.

User-Friendly Interface:-

We have designed a user-friendly web interface that is intuitive, visually appealing, and easy to navigate. Users can focus on their interview preparation without facing any technical issues, ensuring a seamless experience.

Tech Stacks Used

Frontend:-

  • React with TypeScript: We chose React for its component-based architecture, which helps create a modular and scalable user interface. TypeScript adds static typing, enhancing code robustness and maintainability.

  • Tailwind CSS: Tailwind CSS provides a utility-first approach, making it easier to create consistent and responsive designs. It simplifies styling and allows us to maintain a visually appealing interface.

Backend:-

Java Spring Boot: Spring Boot offers a powerful and feature-rich framework for building Java-based web applications. It provides robust tools for handling backend functionalities.

AI Integration:-

We leverage the power of the OpenAI API to enable dynamic question generation and lifelike interactions with the AI interviewer. The OpenAI API helps us create engaging and intelligent conversations with users, enhancing their interview preparation experience.

Contributors

Veerangana Malav

Github: VeeranganaMalav

Suraj Deosarkar

Github: Suraj12398

Ajit Kumar Roy

Github: Ajitroy01

Md Abdul Qadir

Github: Md-abdul

Shivam Kumar Jha

Github: Shivam6209

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AI-powered self-interview preparation platform. This platform will use the magic of AI and language processing to simulate real interview scenarios. It will give users feedback on their responses and provide helpful resources and suggestions to enhance their interview skills.

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  • TypeScript 71.3%
  • CSS 12.5%
  • Java 8.5%
  • HTML 4.0%
  • JavaScript 3.7%