Computer Science Graduate | AI, Machine Learning & Software Development · Giza
Computer Science graduate with hands-on experience in Artificial Intelligence, Machine Learning, Data Science, Software Development, and backend technologies. Built practical projects involving Computer Vision, NLP, data analytics, mobile applications, APIs, databases, and cybersecurity.
Training in Machine Learning, Data Science, and practical AI applications Working with Python, Scikit-learn, Pandas, NumPy, TensorFlow, and PyTorch Gaining hands-on experience in real-world AI projects
Training in Generative AI, LLMs, RAG, and Agentic AI Working with LangChain, LangGraph, and Vector Databases Developing skills in advanced AI technologies
Completed practical training in Generative AI and advanced AI concepts Gained experience in AI model development and implementation Collaborated with a team on AI-driven projects
Completed a practical Machine Learning internship program Worked on real-world machine learning problems Gained exposure to various ML algorithms and tools
Completed Machine Learning summer training with 90 technical hours and 30 freelancing hours Focused on hands-on projects and practical applications of ML Enhanced understanding of machine learning frameworks and methodologies
Built and integrated a face recognition workflow for comparing uploaded images against stored database records, returning possible matches and confidence scores for missing-person identification use cases Worked on practical AI integration with backend APIs, image storage, and mobile application flow to support accurate matching and user notifications
Technologies: Python, Flask, Computer Vision, Face Recognition, MongoDB, React Native, Node.js, Express.js, Cloudinary, REST APIs
Developed an AI-powered web application that summarizes YouTube videos and generates automated questions using NLP models to support faster learning and content understanding
Technologies: Python, Streamlit, NLP, Hugging Face/Transformers, YouTube transcript processing
Developed a data analysis and classification system for large-scale customer complaints, including preprocessing, cleaning, insight extraction, and dashboard visualization for data-driven decisions
Technologies: Python, Pandas, NumPy, Data Cleaning, Classification, Data Visualization, Streamlit
Designed and developed a system analysis project for an online pharmacy mobile app, supporting product browsing, pharmacy workflow concepts, and AI-assisted features using OpenAI integration
Technologies: React Native, Firebase, OpenAI API, System Analysis, Mobile App Design
Designed a cybersecurity workflow covering the prevention side of security through system hardening: reducing attack surface, securing SSH configuration, disabling unsafe access, and applying CIS benchmark concepts Documented incident response investigation steps using the PICERL lifecycle, including identification, containment, eradication, recovery, lessons learned, endpoint checks, log/SIEM concepts, and network traffic inspection
Technologies: Linux, Bash, PowerShell, CIS Benchmarks, OpenSCAP, GPO concepts, SIEM/ELK, Wireshark, Incident Response
Implemented and analyzed an IPsec VPN tunnel using strongSwan to secure communication between private networks, comparing Tunnel Mode and Transport Mode Inspected ESP packets in Wireshark, analyzed SPI, sequence numbers, SAD/SPD behavior, and tested anti-replay protection using tcpreplay
Technologies: IPsec, strongSwan, Linux, Wireshark, ESP, SAD, SPD, tcpreplay