Myself
Welcome, brilliant soul! 😊I’m Mohammad Ibrahim, a Software Engineer passionate about technology, Graduated from East Delta University with a Bachelor of Science in Computer Science & Engineering in May 2024, achieving a GPA of 3.59 and receiving the Dean's List Award 7 times.I specialize in JavaScript, NextJs, React.js, Node.js, and MongoDB, with extensive hands-on experience in MERN web development.Currently, I serve as the Developer for PoshKits, leveraging my expertise in digital marketing and technical skills to expand our E-commerce clothing business.Additionally, I've participated in numerous online programming contests, honing my problem-solving abilities through a variety of challenges.Let's collaborate to create something extraordinary!I’m always on the lookout for new learning opportunities and challenges. Feel free to explore my projects and resume for more details!You can see my resume here.
Projects
PoshFoods
Features:
- Personalized dashboard for users to manage their accounts and shopping experience.
- Efficient order management for administrators to handle orders seamlessly.
- Product reviews and ratings to improve customer engagement.
Technologies:
- NextJs
- React
- Node.js
- Express
- MongoDB
- TailwindCSS
PoshTurf
Features:
- Real-time booking system for turf and sports facilities.
- Administrator dashboard to manage bookings and facilities.
- Responsive design for optimal performance on all devices.
Technologies:
- React
- TypeScript
- Node.js
- Express
- MongoDB
TukiTaki
Features:
- Buy and sell platform for used mobile phones.
- Secure transactions between buyers and sellers.
- User-friendly interface designed for ease of use.
Technologies:
- React
- Node.js
- Express
- MongoDB
- Firebase
Code for Chill
Features:
- Fun and realistic programming tutorials designed with students in mind.
- Interactive learning with a focus on practical coding challenges.
- Wide variety of programming languages to help students learn effectively.
Technologies:
- React
- Node.js
- Express
- MongoDB
- TailwindCSS
Skin-Cancer-Prediction
Features:
- AI-driven skin cancer classification for three common cancer types.
- Image preprocessing and feature extraction for accurate results.
- Web-based app that allows users to upload images for detection.
Technologies:
- Python
- TensorFlow
- Google Colab
- Flask
