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Registration: 08.08.2026

Shehab Mansour

Specialization: Python Developer
— Back-End Developer specializing in Python and Django with focus on AI-integrated web systems and IoT applications. — Developed Easy Cart, an AI-powered smart retail system using Django REST Framework, YOLOv8 object detection, and Raspberry Pi. — Experienced in building REST APIs with JWT authentication, MySQL/SQLite databases, and real-time data processing. — Proficient in machine learning and AI deployment: YOLOv8, OpenCV, PyTorch, Scikit-learn. — Solid experience in embedded systems and IoT: Arduino, ESP32, Raspberry Pi. — Delivered 50+ Arduino training sessions to students aged 12–22. — Academic background in CCNA-level networking, data mining, and operating systems.
— Back-End Developer specializing in Python and Django with focus on AI-integrated web systems and IoT applications. — Developed Easy Cart, an AI-powered smart retail system using Django REST Framework, YOLOv8 object detection, and Raspberry Pi. — Experienced in building REST APIs with JWT authentication, MySQL/SQLite databases, and real-time data processing. — Proficient in machine learning and AI deployment: YOLOv8, OpenCV, PyTorch, Scikit-learn. — Solid experience in embedded systems and IoT: Arduino, ESP32, Raspberry Pi. — Delivered 50+ Arduino training sessions to students aged 12–22. — Academic background in CCNA-level networking, data mining, and operating systems.

Skills

Python
Django
Django REST Framework
MySQL
REST API
YOLOv8
Machine Learning
OpenCV
PyTorch
Raspberry Pi
Arduino
JavaScript
PHP
Java
C
Git
Linux
SQLite
JWT Authentication
Scikit-learn
Data Mining
ESP32
HTML
CSS
Postman

Work experience

Backend Developer
2024 - 2025 |El-Shorouk Academy
Django REST Framework, Python, MySQL, SQLite, YOLOv8, OpenCV, Raspberry Pi, JWT Authentication
● Led backend development of Easy Cart, an AI-powered smart retail shopping cart system. ● Implemented REST APIs for product management, real-time cart tracking, checkout, and analytics. ● Integrated YOLOv8 object detection on Raspberry Pi for real-time product recognition. ● Developed indoor navigation via IPS using RSSI and A* pathfinding algorithm. ● Built load sensor integration, QR login system, API sync, and admin dashboard.
Arduino Workshop Instructor
07.2024 - 02.2025 |University Arduino Workshop
Arduino, C, Electronics, Sensors
● Delivered 50+ session course to teens aged 12–22 on embedded systems and Arduino projects. ● Covered sensors, actuators, C programming, and real-world applications.

Educational background

Computer and Control Engineering (Bachelor’s Degree)
2020 - 2025
El-Shorouk Academy

Languages

ArabicNativeEnglishUpper Intermediate