Fourth-year Computer Science student at Cairo University with strong foundations in software engineering, backend development, and machine learning fundamentals. I have hands-on experience building production-ready backend systems, implementing data-driven applications, and working with core ML concepts such as model evaluation and exploratory data analysis. Selected as a Machine Learning Ambassador from 2,000+ applicants at GTC, and previously completed an iOS Internship at Banque Misr.
🔗 Portfolio: https://ahmed-nasser-portfolio.vercel.app/
- 🎯 Current Focus: Backend Engineering & Machine Learning Systems
- 💡 Interests: Scalable Backend Systems, Data-Driven Applications, Applied ML
- 🎓 Education: B.Sc. in Computer Science — Cairo University
+ Algorithms & Data Structures
+ Object-Oriented Programming (OOP)
+ SOLID Principles
+ Design Patterns
Machine Learning Ambassador @ GTC
📅 Sep 2025 – Oct 2025
+ Selected from 2,000+ applicants to represent the ML community
+ Participated in technical discussions and ML knowledge-sharing initiatives
+ Supported peers in understanding core ML concepts and applications iOS Internship @ Banque Misr
📅 Aug 2024 – Sep 2024
+ Developed production-level mobile features in an agile environment
+ Integrated RESTful APIs for data-driven application behavior
+ Improved usability and performance through iterative optimization
Hands-on machine learning journey with from-scratch implementations and reproducible experiments.
Highlights:
- Documenting my end-to-end Machine Learning learning journey
- Hands-on experimentation to build strong ML foundations
- Personal reference and growing public portfolio for ML studiesStatistical analysis of movie rating systems
Analysis:
- Comprehensive exploratory data analysis
- Statistical pattern visualization
- Rating distribution comparisonsRESTful blogging platform with modern authentication
Features:
- JWT authentication & role-based access
- CRUD posts with relational voting system
- PostgreSQL, SQLAlchemy ORM, Alembic migrations
- Pytest test suite & Docker supportModular Java library implementing Neural Networks, Fuzzy Logic, and Genetic Algorithms with case studies.
Components:
- Fuzzy Logic: rule engine, membership functions, defuzzification
- Genetic Algorithms: selection, crossover, mutation
Case Studies:
- Job Scheduling (GA)
- Automatic Window Blind Control (Fuzzy Logic)Explore my full portfolio for projects, skills, and contact details:
🔗 https://ahmed-nasser-portfolio.vercel.app/
- 🤖 Machine Learning Specialization - DeepLearning.AI & Stanford University
- 📊 Forward Program - McKinsey & Company