AI-Powered Career Recommendation System

Problem statement

Students often struggle to choose suitable careers due to lack of personalized guidance. Traditional counseling is limited and cannot scale to thousands of students. A data-driven recommendation engine can help students make informed decisions.

Abstract

This system collects inputs such as academic performance, skill ratings, interest surveys, personality traits and extracurricular involvement. ML models like KNN or clustering algorithms group students with similar profiles and recommend suitable education or career paths. The dashboard presents career strengths, recommended roles and required skills to focus on.

Components required

• Python + Scikit-Learn
• Survey form & data collection
• Dataset for training (skills, careers mapping)
• Web dashboard
• Optional personality test API integration

Block diagram

Working

Students enter academic scores, interests, skills and personality traits. The model processes this data and predicts suitable domains such as software, design, research, marketing, etc. The dashboard displays career matches, skill gaps and suggested learning resources.

Applications

• Schools and colleges
• Career counseling centers
• Online learning platforms
• Personal career planning