International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 10 | Oct 2024
p-ISSN: 2395-0072
www.irjet.net
AI-POWERED PLATFORM FOR PERSONALIZED INTERVIEW PREPARATION, SKILL EVALUATION, AND FEEDBACK GENERATION Fiza Tamboli1, Rutuja Terdale2, Isha Patil3, Pragati Chougule4, Sejal Bagadi5, Ms. M. T. Naik6. *1,2,3,4,5 Department of Computer Science & Engineering, Yadrav (Ichalkaranji) Maharashtra, India.. *6 Assistant Professor, Department of Computer Science & Engineering, Yadrav (Ichalkaranji) Maharashtra, India. ---------------------------------------------------------------------***--------------------------------------------------------------------personalization, interaction, and immediate feedback, are Abstract - The creation of an AI-powered platform for
addressed by our platform. It enables users to safely sign up or log in, select a role for which they wish to prepare, and get customized interview questions. It also offers performance analytics and feedback for ongoing development. Such a system can readily scale and be updated with the most recent inquiries and market trends thanks to the development of AI tools and cloud platforms. It is impossible to overestimate the significance of interview preparation in the cutthroat job market of today. In addition to technical expertise, employers are increasingly seeking applicants who can communicate effectively, solve problems, and show domain knowledge in an interview. Through the simulation of a real-world setting, our platform acts as a bridge to assist candidates in achieving these competencies. The system guarantees secure data handling and smooth integration by utilizing technologies such as TypeScript, React, Firebase, and Gemini AI. In conclusion, the platform offers a comprehensive, AI-powered solution to raise job seekers' general level of preparedness.
interview preparation is presented in this report. By letting users log in, choose a role, practice interview questions, and get feedback, the platform helps users get ready for interviews. TypeScript, Gemini, Firebase, React, HTML, and Talwind CSS are all part of the technology stack. By offering a simulated experience that closely resembles actual interview circumstances, this platform seeks to transform interview preparation. It uses AI to tailor question sets according to specific roles and offers thorough feedback to improve user performance. Key Words: Interview preparation, AI based Learning, Voice Assistant, Skill Development, Prompt.
1.INTRODUCTION For job seekers, it is essential to prepare for interviews. By assisting users with practice interviews, AI-powered platforms can greatly enhance this process. By mimicking an actual interview, this project seeks to create an effective platform that aids users in getting ready for job interviews. The shortcomings of conventional preparation techniques, which frequently lack personalization, interaction, and immediate feedback, are addressed by our platform. It enables users to safely sign up or log in, select a role for which they wish to prepare, and get customized interview questions. It also offers performance analytics and feedback for ongoing development. Such a system can readily scale and be updated with the most recent inquiries and market trends thanks to the development of AI tools and cloud platforms It is impossible to overestimate the significance of interview preparation in the cutthroat job market of today. In addition to technical expertise, employers are increasingly seeking applicants who can communicate effectively, solve problems, and show domain knowledge in an interview. Through the simulation of a real-world setting, our platform acts as a bridge to assist candidates in achieving these competencies. The system guarantees secure data handling and smooth integration by utilizing technologies such as TypeScript, React, Firebase, and Gemini AI. In conclusion, the platform offers a comprehensive, AI-powered solution to raise job seekers' general level of preparedness. For job seekers, it is essential to prepare for interviews. By assisting users with practice interviews, AI-powered platforms can greatly enhance this process. The shortcomings of conventional preparation techniques, which frequently lack
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Impact Factor value: 8.315
1.1 SYSTEM ARCHITECTURE The AI-powered platform for interview preparation has a modular, scalable, and secure system architecture. It is made up of a number of essential parts that cooperate to give the user a seamless experience. React and HTML/CSS are utilized at the front-end to create a user interface that is responsive and easy to use. A solid foundation for codebase maintenance with strong typing is offered by TypeScript. Firebase manages databases and authentication, guaranteeing safe user data retrieval and storage. The feedback and question-generation modules are powered by Gemini AI, which customizes content based on the role the user has selected. The client application interacts with the backend services through secure APIs in this client-server architecture. RESTful endpoints allow data to move between components with ease. Additionally, cloud-based deployment is used by the system to guarantee. Additionally, cloud-based deployment is used by the system to guarantee scalability and high availability. Sensitive data encryption and Firebase authentication are used to guarantee security. The system architecture is essentially designed to support multiple users at once with minimal latency and maximum dependability. The AI-powered platform for interview preparation has a modular, scalable, and secure system architecture. It is made up of a number of essential parts that cooperate to give the
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