About Me
Good experience with Machine Learning and Data Science. Completed various projects using
different algorithms and datasets. Skilled in Natural Language Processing (NLP), Transformer
models, and fine-tuning. good experience in Power BI, Pandas, and software engineering with a
focus on backend using FastAPI and MySQL. Kaggle Notebook Expert
and current Full stact Data Scientist intern at Fixed Solutions.
Education
Bachelor of Computer Science (2018 – 2022)
Elshrouk Academy for Computer and Information Science
Experience
Full Stack Data Scientist Intern — Fixed Solution (July 2025 – Present)
- Built AI agents using n8n triggers.
- Developed classic ML models and built Docker images.
- Deployed APIs using Flask.
- Developed RAG chatbot that supports multi domains.
ML for Data Analysis — NTI Digital Egypt Youth (Dec 2024 – Jan 2025)
- Worked on ML models and preprocessing.
- Competed in Kaggle competition “Home Credit Risk”.
Freelance Data Analyst — FreelanceYard (Apr 2025 – Present)
- Built interactive sales dashboards in Power BI.
- Crafted KPIs using DAX (avg. unit price, quantity sold, discount distribution).
Technical Skills
- Data Science: ML, DL, NLP, LLM, Python (Pandas, NumPy), Keras, Scikit-learn, Fine-tuning, RAG
- Data Analysis: Power BI, Excel, MySQL, Matplotlib, Seaborn
- Software: Data Structures, OOP, Docker, Laravel (Backend), FastAPI
Projects
- RoboFaults
Worked on a robot fault detection dataset to classify normal vs. fault states across six joints. Identified temperature and current as the most critical factors influencing robot faults
[GitHub]
- Nurse Robot (Graduation Project)
Robot to assist doctors during COVID using QR and face recognition. Website + mobile app for control.
Grade: Excellent.
- CIBMTR – Survival Prediction (Kaggle)
Achieved 63% score on survival prediction. Used CatBoost, XGBoost.
[Kaggle Notebook]
- Medical Chatbot (LLM Fine-Tuning)
Fine-tuned TinyLlama-1.1B on HealthCareMagic-100k using LoRA. Deployed with Gradio for real-time Q&A.
[GitHub]
- Autocomplete System
LSTM-based autocomplete with NLP preprocessing. Also tried GloVe embeddings. Frontend in Streamlit.
[GitHub]
- Autonomous Web Research Agent
AI agent for autonomous scraping. Integrated with n8n triggers.
[GitHub]
- Chatbot RAG System
Multi-domain chatbot with vector DB embeddings, chat history, Flutter frontend + FastAPI backend.
[GitHub]
- Marketing Campaign ML Model
Built and evaluated ML models to predict customer responses to marketing campaigns. Applied preprocessing, feature engineering, and multiple algorithms to improve prediction accuracy.
[GitHub]
Languages
- Arabic — Native
- English — B2