OpportuNest - Campus Career Management System

Becoming well settled in placements is quite difficult for a student in today's job market scenario as it is very competitive. Placement cells have a lot of data regarding the students as well as job openings to be collected. Most of these methods are traditional and very slow and tend to make mistakes, because of which there are missed opportunities for both students and companies. Being completely online, the OpportuNest project will build a very efficient platform that shall focus on streamlining processes, reviewing CV s with machine automation and making predictions on placements. Highly capable modern web technolo-gies would be employed to make the entire placement process simpler, from the sophisticated machine learning algorithms on the MERN stack to assistance for administrators and placement officers. Some of the additional benefits will include ATS scoring for resume optimization, real-time data analysis for displaying metrics of performance, AI-based job matching according to skills and qualifications of the user, and improved user experience with personalized dashboards. All of that can be achieved thanks to effective, transparent, and user-friendly components in OpportuNest's career placement environment. The practice aptitude tests score based on the Random Forest algorithm to determine the placement probability, and an interview mock test feature is available on the student dashboard. For predicting future trends like those pertaining to enrollments and placements, OpportuNest uses an LSTM neural network for analyses based on patterns in historical data. All these features in OpportuNest are meant to enhance efficiency, transparency, and user experience, thus facilitating the smooth and hassle-free placement process for both administrators and students.