Скачать или смотреть SIH25034 - Al-Based Internship Recommendation Engine for PM Internship Scheme

Background

The PM Internship Scheme receives applications from youth across India, including rural areas, tribal districts, urban slums, and remote colleges. Many of these candidates are first-generation learners with limited digital exposure and no prior internship experience. With hundreds of internships listed on the portal, it becomes difficult for such candidates to identify which ones match their skills, interests, or aspirations. This leads to misaligned applications and missed opportunities.

Description

The problem seeks to build a simple, lightweight AI-based recommendation engine that suggests the most relevant internships to each candidate based on their profile, academic background, interests, and location preferences. The system should be user-friendly, mobile-compatible, and work well even for users with low digital literacy. It should offer 3-5 personalized suggestions, instead of a long list, and help candidates make informed choices. The tool must be simple enough to be integrated with the existing PM Internship Scheme portal and must avoid complex or resource-intensive deployment.

Expected Solution

A functional prototype that:
• Captures basic candidate inputs (education, skills, sector interests, location)
• Uses a rule-based or ML-light model to suggest 3-5 top internships
• Has a simple, intuitive UI with minimal text and visual cues
• Can be accessed on mobile devices and adapted to regional language use
• Outputs recommendations in a clear, user-friendly format (e.g., cards or simple list)