AI-Powered Scholarship Intelligence and Career Recommendation Platform

AI-Powered Scholarship Intelligence and Career Recommendation Platform

Finding the right scholarship is one of the most stressful parts of a student's academic journey. There are hundreds of scholarships, each with its own eligibility rules, and most students never discover the ones they actually qualify for. This final year project solves that problem with a single intelligent platform. A student fills one profile form, and the system tells them which scholarships they are eligible for, which ones suit them best, how likely they are to succeed, and which career paths and skills match their profile. Every result is backed by a clear, visual explanation so nothing feels like a black box.

Built with Python and Flask and trained inside well-documented Jupyter notebooks, this is a strong, defensible choice for computer science and IT students who want a project that goes beyond a simple prediction model. It combines classification, recommendation, ranking, and explainable AI into one connected product, which makes it stand out in viva and on a resume.

Key Features

• Eligibility Prediction: A trained Random Forest classifier decides whether a student qualifies for each scholarship and returns a confidence score.
• Scholarship Recommendation: Content-based filtering with cosine similarity matches the student profile to the most relevant scholarships, with clear reasons for each match.
• Scholarship Ranking: A transparent weighted scoring system re-ranks results using match strength, success probability, award amount, and deadline urgency.
• Success Probability Prediction: A probability model estimates the realistic chance of winning each scholarship and shows it as an easy-to-read percentage.
• Career and Skill Recommendations: The platform suggests the top career paths for the student and the skills needed to get there, with an optional AI-generated learning roadmap.
• Explainable AI Dashboard: SHAP-powered charts reveal exactly which factors drove each prediction, turning the whole system into something a student can confidently defend.

Applications

• College and university scholarship cells that want to guide students automatically.
• EdTech platforms looking to add a smart scholarship matching feature.
• Career counselling tools that pair financial aid guidance with skill planning.
• A complete, demo-ready academic submission for final year and major project work.

What You Get

The package includes the full source code, the training notebooks for every model, a synthetic data generation script, a clean and professional dashboard interface, an SQLite database, and a step-by-step setup guide. The platform runs completely offline, with the AI career roadmap as an optional add-on, so your demo never depends on an internet connection.

If you want to explore more options in this space, you can browse our full collection of AI and machine learning final year projects, or view every available build on the final year projects with source code page.

Why This Project Stands Out

Most student projects stop at a single prediction. This one tells a complete story: it predicts, recommends, ranks, estimates outcomes, plans a career, and then explains itself. That combination of practical value and explainability is exactly what evaluators look for, and it gives the student plenty to talk about during the viva.