DATA ANALYIST

"Using AI Algorithms for predicting Student Academic Performance" examined actual educational data from Kaggle. used and contrasted a number of machine learning algorithms, including SVM, Random Forest, XGBoost, Neural Networks, and Decision Trees. interpreted model behavior and produced useful educational insights using Explainable AI (XAI) techniques such as SHAP values. In addition to my expertise in data preprocessing, model evaluation, feature engineering, and result visualization, I possess strong technical skills in Python (Pandas, Scikit-learn, XGBoost, Matplotlib, and Seaborn). I have a strong interest in using AI-powered and data-driven solutions to address practical issues and encourage well-informed decision-making.