🔍 What Inspired Us Preparing for technical interviews can be overwhelming for many CSE students, especially without proper guidance or access to real mock interview environments. We wanted to create a smart, accessible tool that simulates real interview experiences and provides personalized feedback to help students improve their confidence and communication skills — all powered by AI.
💡 What We Learned How to use Flask to build a web-based application Basics of Natural Language Processing (NLP) to analyze interview answers How to integrate AI for generating questions and evaluating responses Understanding user experience from a student’s perspective The value of combining technical skills with real-world problems
🛠️ How We Built It Used Python Flask as the backend framework Created a chat-style interface using HTML, CSS, and Jinja templates Added a question bank based on job roles like Frontend, Backend, and Data Science Implemented text-based response collection and feedback system Planned for future enhancements like voice input and OpenAI GPT integration
🚧 Challenges We Faced Designing a simple yet interactive user interface Creating relevant and diverse interview questions for different roles Providing meaningful feedback without advanced AI in the early prototype Managing state across user sessions in a stateless web environment Time management — balancing feature development with presentation preparation
Built With
- database
- python
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