Analysis of Campus Placement Data: A Case Study

One of the main goals of the educational institution is the placement of students. An institution's reputation and annual enrolment rely inevitably on their students' placements. Analyzing the proportion of campus placements is one of the primal factors that students consider when selecting and applying to colleges. That is why all the institutions work hard to develop their organization in its entirety by strengthening the placements department. Any help in this specific field would have a positive effect on the campus placements. The students as well as the institution will benefit from this. In this context, the strategy is therefore to analyze and forecast the importance of campus placements, which not only help strengthen an institution’s reputation but also optimize placements for students. Data pertaining to the study was collected from the institution for which suitable Data pre-processing methods like data blending, data Transformation, removing noise and inconsistencies are applied in order to analyze and mine useful insights which are then visualized in the form of an interactive dashboard. The charts surfaced in different formats offer concise ways to express the change in the placements in the past 11 years. To further aid this process, previous data has been used for future placement prediction using Machine Learning. Models are developed using the classification algorithms - Support Vector Machine, K- Nearest Neighbor, Decision Tree, Random Forest and Naive Bayes algorithm to validate the approaches.