Our nation loses a lot of resources when a child quits school. Finding a method to lower the dropout rate will benefit society and the nation. To help the government address the causes of dropout, data scientists have tried to forecast the number of students who will leave school in a given year and the number of students who will leave a specific school or region.

Four of the major issues we found in the education sector's concerns are addressed in this study by the use of data science. As an illustration, we might observe that kids with a high likelihood of dropping out throughout an academic year could be anticipated if several causes causing school dropout could be identified and the data could be collected using an acceptable mechanism. Similarly to this, if the right machine learning algorithm is applied, a student's learning difficulty can be accurately detected.

Although the evaluation of teachers and students using data science has some limits, greater research in the field and more sophisticated and scientific data collection techniques could provide more insight into how to address such issues. In this article, we saw how data science might be used to address some of the problems in the education sector. This work should be viewed as a preliminary step before more extensive research on this topic is done in the near future. Furthermore, if you are someone interested in learning more about tools used by data scientists in various sectors, join Learnbay. It offers the [url]best data science courses in India[/https://www.learnbay.co/best-data-science-courses-in-india] for working professionals of all backgrounds.