Sadia Afzaal
Web and App developer building modern and responsive designs
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THE AuraBeats is a Shopify-powered online store that blends immersive audio gear with a calming, energy-enhancing aesthetic. Focused on wireless headphones, earbuds, and portable speakers, the project targets listeners who want both premium sound and a mood-boosting design—whether for work, travel, or relaxation. Currently in a password-protected preview phase, the store is building anticipation for a curated, exclusive launch that prioritizes atmosphere alongside audio quality.
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This is a personal portfolio website for Sadia Afzaal, a web developer and frontend designer. Built with HTML, CSS, JavaScript, and jQuery, the site features a responsive navbar with smooth scrolling, a hero section with a typing animation that cycles through roles like "Web Developer" and "Freelancer," an about section with a profile image and bio, services cards for Web Design, Advertising, and Apps Design, a skills section with percentage bars for HTML, CSS, JavaScript, PHP, and MySQL, a team carousel showcasing five team members, a contact form, and a scroll-to-top button. The design uses a dark theme with crimson red accents, and the site is fully responsive across all devices.
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This is a complete frontend salon booking website built with React.js, featuring a pink luxury theme and eight responsive pages: Home (hero, services, stylists, doorstep services), Services (sidebar menu with 13 service categories and pricing tables), Stylists (searchable/filterable directory with 9 individual profile pages), Gallery (filterable image grid with lightbox), About (stats and values), Contact (form with FAQ accordion), and a 4-step booking wizard with validation, progress indicator, sticky summary, and confirmation screen. The project uses React Router, Font Awesome icons, CSS modules, and a consistent design system with glass morphism effects, smooth animations, and fully responsive layouts ready to connect to a backend API.
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Developed a full-stack fraud detection web app as part of an ML course project. Built the backend in Python/Flask with 5 machine learning models for transaction classification, and the frontend in React.js with a real-time dashboard, alert system, and report generation. Integrated SQLite for data storage and connected everything through a REST API.
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