01
AI & Data Science Enthusiast
Turning data into smarter decisions.
I'm Ahmed Hussein, a Computer Science student specializing in Artificial Intelligence, with hands-on experience in Python, Machine Learning, Data Science, and Data Analysis.
PythonMachine LearningData ScienceAI
Available for opportunities & collaboration
MLMachine Learning
DSData Science
PYPython
01 / About
Building with data, learning by doing.
Computer Science student specializing in Data Science and Artificial Intelligence, passionate about building intelligent solutions that solve real-world problems.
Strong in problem solving, teamwork, adaptability, and continuous learning, with a growth mindset and a focus on becoming a Data Scientist and AI Engineer.
02 / Education
Academic foundation.
09/2024 — Present · Giza, Egypt
Bachelor's Degree in Computer Science — Artificial Intelligence
October 6 University · Faculty of Computers and Information
Computer Science
Artificial Intelligence
Artificial Intelligence
03 / Experience
Currently in the field.
DEPI
07/2026 — 12/2026 · Cairo, Egypt
AI & Data Science Track Intern
Digital Egypt Pioneers Initiative (DEPI)
- Training on applied Machine Learning and Data Science workflows as part of a structured, industry-aligned track.
- Building practical skills in Python, data analysis, and model development through guided projects and coursework.
04 / Skills
The tools I use to build.
02
Data Science & Analysis
03
Machine Learning
04
Visualization & Explainability
05
Deployment & Tools
06
Computer Science
Soft skills
Problem Solving · Analytical Thinking · Teamwork · Collaboration · Communication · Initiative · Adaptability
Languages
Arabic · English
05 / Projects
View GitHub ↗Selected work & real builds.
★ Featured project
Python · XGBoost · Scikit-learn · SHAP01
Credit Risk Prediction
End-to-end ML pipeline on 150,000 customer records, engineering 13 final features while handling a 93.3% / 6.7% class imbalance.
0.62Recall
13Features
150KRecords
SHAP explainabilityFastAPIStreamlit
How it works
From raw records to an explainable decision.
- Clean — fixed invalid entries and traced an extreme DebtRatio pattern to missing income.
- Engineer — combined late-payment counters into TotalTimesLate, raising correlation from 0.31 to 0.39.
- Compare — evaluated Logistic Regression, Random Forest, and XGBoost using Recall and F1.
- Explain — used SHAP to identify Total Times Late and Credit Utilization as key risk drivers.
- Deploy — shipped the final model with FastAPI and Streamlit.
02 · Python
AI Fitness Coach
Calculates daily calorie, water, and protein requirements from user metrics including BMI, then uses an AI model for personalized recommendations.
03 · Java
Drawing App
Desktop drawing application built with Java and Object-Oriented Programming principles, including user interactions and drawing functionality.
06 / Contact
Have a project in mind? Let's build.
Open to internships, junior opportunities, collaboration, and interesting AI & Data Science projects.