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Prashikshan: A Centralized Academia–Industry Interface for Internship and Skill Validation

Dr. Devidas Thosar, Trisha Gujjula, Tanishka Devgirkar, Veenit Ramteke, Lakshmi Sharma, Girish Patil, Anjali Gaur

Abstract


Prashikshan is an AI-driven academia–industry interface system designed to bridge the gap between academic learning and industry requirements. The platform evaluates student competencies by analyzing academic records, certifications, and project experience using machine learning algorithms such as Random Forest and Neural Networks. Based on this analysis, the system identifies skill gaps and provides personalized recommendations to enhance employability. It also automates internship matching by aligning validated student skills with industry requirements through a centralized and transparent process. The architecture consists of a student dashboard, institutional admin panel, industry portal, AI processing module, and secure cloud-based database. By integrating web technologies, machine learning models, and role-based authentication, the system ensures scalability, efficiency, and data security. Prashikshan reduces manual workload, improves internship allocation accuracy, and strengthens collaboration between institutions and industry partners, contributing to a smarter and more data-driven educational ecosystem.


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