Prediction of admission and jobs trends in the field of engineering and technology, pharmacy and management based on the demographic location

India faces a significant challenge with rising unemployment, exacerbated by a lack of awareness among students regarding career prospects. The gap between current undergraduate and postgraduate courses and market demands adds to the issue. This study addresses the disparity by utilising machine learning models, including multiple linear regression, KNN, random forest, and XGBoost. By predicting future job trends, admissions, and placements, the integrated system aims to guide students in making informed course choices. Additionally, the research addresses the shortage of relevant datasets by creating a comprehensive dataset encompassing India's state-wise admission and placement, Gujarat District-level data, state-wise start-up information, and educational institutional analysis, compiled from diverse sources.