Predict Students Dropout and Academic Success Using Machine Learning Algorithms

This project understands how the student's performance (test scores) is affected by other variables such as Gender, Ethnicity, Parental level of education, Lunch and Test preparation course

🎓 Leveraging for containerization and CI/CD pipelines. It includes code and configuration files for seamless development and deployment processes.

Analyse performance of students on the basis of their personal life style, studying style, family related, educational environment satisfaction, students grades using ML model

TDT4173 project

To understand the how the student's performance (test scores) is affected by the other variables (Gender, Ethnicity, Parental level of education, Lunch, Test preparation course).

This project analyzes student performance data to evaluate whether test preparation courses have a measurable impact on math scores. It involves data cleaning, EDA, visualizations, and hypothesis testing using Python libraries.

Exploratory Data Analysis and preprocessing on Students Performance dataset. Covers variance-based feature selection, missing value handling, IQR-based outlier removal on math and reading scores.

Three-part student data analysis project covering data cleaning and column renaming, feature engineering with total score calculation, and hypothesis testing to check if studying 10+ hours impacts math scores.

Analytical study exploring how demographic, behavioral, and academic variables impact student performance.

Application for university teachers, students or administration, which will help them to check and monitor the academic performance of students, student groups etc. with dashboard of reports and infographics.

Scholar Guide aims to provide proper mentorship to students who want to excel but cannot find a suitable mentor.

Using data to understanding student performance in schools considering factors such as parental level of education, gender, lunch type and test preparation course.

AI-powered teacher assistant that monitors student focus and engagement in real-time