Expertise
Data Analysis & Visualization
Expertise in cleaning, analyzing, and visualizing complex datasets to uncover trends and insights using industry-standard tools.
Machine Learning & Predictive Modeling
Proficient in designing and implementing end-to-end machine learning pipelines, feature engineering, and developing robust predictive models.
Data Science Fundamentals
Strong foundation in core data science principles, including statistics, data preprocessing, and problem-solving methodologies.
Projects
Nobel Prize Winners Analysis
Created insightful visualizations and published a comprehensive report on GitHub.Analyzed over 100 years of Nobel Prize data using Python, Pandas, and Seaborn to uncover trends in U.S. Nobel Prize winners.
FIFA Player Value Prediction
Achieved 96.0% R² and 85.6% classification accuracy using feature engineering and ensemble learning.Designed an end-to-end machine learning pipeline to predict FIFA player market values and classify performance levels.
House Price Prediction
Developed linear regression models from scratch, achieving a test R² of 0.85, and managed team tasks.Led a 10-member team in a machine learning project to predict house prices using the Ames Housing dataset.
Timeline
Completed 5+ hands-on projects in data analysis using Python and SQL during Data Analyst Trainee role.
Gained practical experience in cleaning, analyzing, and visualizing datasets with Python, Tableau, and Power BI.
Commenced Bachelor in Data Science at Alexandria University.