An Intelligent Student Job Prediction using Educational Data Analytics 
Sarvesh T S1, T H Sreenivasa2, Ambika V3
1Sarvesh T S*, Student, Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India.
2Dr. T H Sreenivasa, Professor, Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India.
3Prof. Ambika V, Assistant Professor, Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, India.
Manuscript received on June 01, 2020. | Revised Manuscript received on June 08, 2020. | Manuscript published on June 30, 2020. | PP: 926-930 | Volume-9 Issue-5, June 2020. | Retrieval Number: E9924069520/2020©BEIESP | DOI: 10.35940/ijeat.E9924.069520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Mining of Educational data is an emerging field focused in data mining field to uncover required facts within educational data in order to assist educational institutions to increase their management design also student facilities. It provides essential knowledge about imparting the education, which is used to enhance the quality of teaching and learning. The implementation of the proposed system dataset provides details with respect to old students data. Mining of Educational data is implicated within data mining field to find the required facts inside educational data to assist institutions, to increase the management design along with learner facilities. The present study comes up with applying data science techniques over educational data. Association rule used within student’s data to find some facts for assisting management design. Data Science algorithms implemented by considering grade of courses, also graduated student employment information for job prediction after completion of education. The outcome of this study gives better knowledge for student management design and prediction of job. The main objective of the proposed system is to find the correlations between the student educational parameters with the types of the job.
Keywords: Association Rule; job prediction; classification; Machine Learning.