I’m a junior data scientist with experience in machine learning, data analysis, and end-to-end project development. My work includes classical ML models, ensemble methods, deep learning fundamentals, preprocessing, data wrangling, EDA, and data visualization. I focus on building practical systems that move from raw data to usable insights and deployable applications.
I’m currently combining deep study of ML/math foundations with hands-on project work. I also teach data science topics, including an ongoing data mining series on YouTube, and have delivered private sessions and workshops in programming. I’m in my fourth year studying Computer Science and AI at Helwan University and interested in opportunities related to data and AI.
- Supervised and unsupervised learning
- Feature engineering, model evaluation, and cross-validation
- Ensemble methods and classical ML pipelines
- Deep learning fundamentals using TensorFlow/Keras
- Prompt engineering and structured output design
- Tool-aware agents using LangChain and LCEL
- API-based LLM integrations for automation and data processing
- Building prototypes with OpenAI and Gemini APIs
- Data cleaning, preprocessing, and transformation
- ETL workflows, Selenium scraping, and API collection
- SQL pipelines and database design
- GIS-related data tasks (multispectral preprocessing, GDAL, Rasterio)
- C++ and Java OOP
- Spring Boot basics
- FastAPI microservices
- Dockerized deployments and version control with Git
Programming: Python, SQL, C++, Java
ML & DL: scikit-learn, TensorFlow, Keras, feature engineering, ensembles, evaluation
Data: Pandas, NumPy, ETL, Selenium, SQLAlchemy
Visualization: Matplotlib, Seaborn, Plotly
GenAI & LLMs: LangChain, LCEL, Pydantic, OpenAI API, Gemini API
Tools: Docker, FastAPI, Streamlit, Git, Jira
Statistics: Descriptive statistics, probability fundamentals
- Creator of a Data Mining course on YouTube (8+ hours so far)
- Delivered private sessions in data science and programming (14+ hours)
- Led C++ and Java OOP workshops for university students
- Produced recorded material covering OOP fundamentals and problem solving
