Inspiration

Finding suitable jobs as a fresher can be challenging. Students often struggle to understand job descriptions, identify missing skills, and prepare effectively for interviews. This inspired us to create ApplyWise AI – Intelligent Career Copilot, an AI-powered assistant designed to make career preparation easier and more structured.

What it does

ApplyWise AI aims to help students and fresh graduates: Analyze job descriptions and identify essential skills. Compare resume skills with job requirements. Identify skill gaps and areas for improvement. Generate personalized learning roadmaps. Prepare relevant interview questions based on target roles.

How we built it

We plan to build ApplyWise AI using Python and an NVIDIA open-source AI model accessed through Nebius infrastructure. The application will provide a simple web interface for entering job descriptions and resume information, with an AI backend that generates career guidance. We intend to use FastAPI for backend APIs and Streamlit for the user interface, depending on the final implementation.

Challenges we ran into

As we begin development, our main challenges are learning to integrate the required NVIDIA model with Nebius, designing useful prompts, comparing resume information with job requirements, and ensuring that generated recommendations are relevant and reliable. We also aim to make the application simple for beginners to use.

Accomplishments that we're proud of

We have defined a practical problem to solve and developed a clear project plan for an AI-powered career assistant. We are working toward combining Generative AI with real-world job preparation needs in a project that can benefit students and fresh graduates.

What we learned

Through this project, we aim to gain practical experience with open-source AI models, Nebius infrastructure, Python application development, prompt engineering, API integration, and building an AI-powered application from the ground up.

What's next for ApplyWise AI – Intelligent Career Copilot

Our next steps are to integrate the required NVIDIA open-source model, implement resume and job description analysis, generate personalized skill-gap reports, and build a functional web interface. We also plan to test the application with different job descriptions, improve the quality of recommendations, and deploy a working demo for users.

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