Career Prediction Classifiers based on Academic Performance and Skills using Machine Learning

International Journal of Computer Science and Engineering
© 2022 by SSRG - IJCSE Journal
Volume 9 Issue 3
Year of Publication : 2022
Authors : Akanksha Pandey, L S Maurya

How to Cite?

Akanksha Pandey, L S Maurya, "Career Prediction Classifiers based on Academic Performance and Skills using Machine Learning," SSRG International Journal of Computer Science and Engineering , vol. 9,  no. 3, pp. 5-20, 2022. Crossref,


In the current scenario, the students need to identify their area of interest in an academic field to opt for the right career courses they are interested in and capable of going through. The students have to go through many options to draw a career path. This paper predicts the career an engineering student can select after graduation using machine learning classification techniques based on academic performance and skills. We will describe the machine learning classification techniques to help students support their decision-making. The machine learning algorithms are presented here; we will compare and analyse the classifier’s results developed by this algorithm. We will discuss our classification in machine learning algorithms to predict the career options for engineering students. The different criteria used to scrutinise the results achieved by these classifiers are accuracy score, confusion matrix, heatmap, percentage accuracy score, and classification report. The research objective is to find the factors that can affect students’ decision to choose the right career path using machine learning techniques.


Career, Machine Learning, Prediction, Python, Skills, Supervised Learning.


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