Yousef abdul raouf

fix every it problem in the school ( laptops , procjetors ..)

also Teach Student About AI(Scratch)

Developed a mobile application powered by advanced AI models to understand and interact with visual content.

Key Features:

• Visual Question Answering (VQA): The app analyzes images and answers questions about their content.
• OCR (Optical Character Recognition): Extracts and understands text from images, including documents and signs.
• Visual Dialog: Enables a continuous conversation with the AI about an image, such as asking follow-up questions. Built with a user-friendly mobile interface to demonstrate real-time image processing and AI interaction capabilities.

mobile application that uses image recognition to help blind and visually impaired users understand their surroundings.

Key Features:

• Identifies objects, people, and environments through the phone camera.
• Provides audio feedback to describe the scene to the user.
• Focused on accessibility and real-time assistance for daily life.

E-commerce App

Two-sided app (User & Provider) with API integration, notifications, and BLoC state management.

( E-commerce App )

Designed and implemented key features using Flutter and Dart, including API integration for real-time data retrieval and display. Enhanced the Ul/UX based on the Figma design by optimizing layout, improving navigation, and ensuring a responsive user interface across devices. The project leveraged skills in mobile development, API connectivity, and Ul refinement, resulting in a seamless and user-friendly application.

Studied core topics in artificial intelligence, machine learning, and computer vision. Gained hands-on experience through practical projects involving image recognition, visual question answering, OCR, and mobile AI applications.

• Notifications Handling
• API Integration
• Security Best Practices
• BLoC Pattern for State Management
• Navigation Between Screens
• Clean Code Practices
• Reusable Code Architecture

A comprehensive deep learning course covering fundamental concepts and practical applications.

Explored topics including neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial networks (GAN).

Gained hands-on experience using

TensorFlow/PyTorch to build and train Al models for image recognition and data analysis. Completed practical projects to enhance skills in implementing state-of-the-art deep learning techniques.