Nobel Prize Winners Analysis
Analyzed over 100 years of Nobel Prize data using Python, Pandas, and Seaborn to uncover trends in U.S. Nobel Prize winners.
Impact: Created insightful visualizations and published a comprehensive report on GitHub.
Expertise
Focus areaWhat I doTechnologies
Data Analysis & Visualization
Expertise in cleaning, analyzing, and visualizing complex datasets to uncover trends and insights using industry-standard tools.
PythonSQLPandasMatplotlibTableau
Machine Learning & Predictive Modeling
Proficient in designing and implementing end-to-end machine learning pipelines, feature engineering, and developing robust predictive models.
PythonScikit-learnNumPyMachine LearningPredictive Models
Data Science Fundamentals
Strong foundation in core data science principles, including statistics, data preprocessing, and problem-solving methodologies.
Data ScienceStatisticsData PreprocessingProblem SolvingCritical Thinking
Featured projects
FIFA Player Value Prediction
Designed an end-to-end machine learning pipeline to predict FIFA player market values and classify performance levels.
Impact: Achieved 96.0% R² and 85.6% classification accuracy using feature engineering and ensemble learning.
House Price Prediction
Led a 10-member team in a machine learning project to predict house prices using the Ames Housing dataset.
Impact: Developed linear regression models from scratch, achieving a test R² of 0.85, and managed team tasks.
Career highlights
2025
Completed 5+ hands-on projects in data analysis using Python and SQL during Data Analyst Trainee role.
2025
Gained practical experience in cleaning, analyzing, and visualizing datasets with Python, Tableau, and Power BI.
2024
Commenced Bachelor in Data Science at Alexandria University.