Envisioning Student’s Performance Over Placements into IT Sector

Anticipating student placements is an essential task for educational institutions, as it can help identify students who may need additional support and resources to succeed in their careers. This project aims to predict student placement performance based on academic performance, testing their fundamentals, standardised test scores, and many more. To accomplish this, we collected data from a large sample of students who had appeared for placement training & attended the skill ability test and later analysed their performance concerning these factors. Furthermore, we shall use this data to develop a machine-learning model to predict student performance on placements. The model trains on the collected data and will be able to predict student performance accurately. This model can help educational institutions [1] or organisations to identify students who may be at risk of poor performance on placements and provide them with the necessary support and resources to improve their skills and efficiency.