STUDENT PLACEMENT PREDICTION

Authors

  • M.V.Nagesh Author
  • Boda Sathvik Author
  • Sriya Thaduri Author
  • E.Kavya Author
  • Soppadandi Sirisha Author

Keywords:

Skill Recommendation System,, Job Placement, Competitive Job Market,, Machine Learning Algorithms,, andom Forest Algorithm,Academic Performance,, CGPA, Internship Experiences, Certifications Earned,, Aptitude Test Scores, Soft Skills Ratings,, Skill Gap Identification.

Abstract

The Student Placement Prediction and Skill Recommendation System is an innovative application
designed to assist students in enhancing their employability and securing suitable job placements.
In today's competitive job market, students often face challenges in understanding their strengths,
identifying required skills, and effectively positioning themselves for job opportunities. This
research work aims to address these challenges by leveraging machine learning algorithms to
predict a student's likelihood of placement and recommend skills to improve their employability.
The dataset used in this proposed system comprises various attributes such as academic
performance (CGPA, marks), internship experiences, projects undertaken, certifications earned,
aptitude test scores, soft skills ratings, and extracurricular activities. Leveraging this dataset,
machine learning models, particularly the Random Forest algorithm, were employed to predict the
probability of a student getting placed and the potential offers from different companies based on
their academic, skill, and experiential profiles. Moreover, the system also offers personalized skill
recommendations to students based on their current profile.

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Published

15-01-2025

How to Cite

STUDENT PLACEMENT PREDICTION. (2025). International Journal of Information Technology and Computer Engineering, 13(1), 31-42. https://ijitce.org/index.php/ijitce/article/view/830