Student grade Prediction

This dataset contains semester-wise academic performance data of BTech students from GIET University. It includes the grades of students from their 1st to 4th semesters, along with their corresponding 5th-semester grades. The dataset is intended for use in educational data mining and machine learning applications, specifically for predicting the 5th-semester grades of students based on their past performance.The dataset consists of 379 student records, with each record containing the following attributes:

SEM 1: Grade obtained in the 1st semester.

SEM 2: Grade obtained in the 2nd semester.

SEM 3: Grade obtained in the 3rd semester.

SEM 4: Grade obtained in the 4th semester.

SEM 5: Grade obtained in the 5th semester (target variable for prediction).The grades are represented on a scale of 0 to 10, where 10 is the highest achievable grade. This dataset can be used to develop predictive models for academic performance, identify trends in student performance, and support decision-making in educational institutions.

Keywords:
Grade Prediction, Student Performance, Educational Data Mining, Academic Analytics, Machine Learning, GIET University

Potential Applications:

Predicting student performance in future semesters.

Identifying at-risk students for early intervention.

Analyzing trends in academic performance over time.