First project using winform

Login using ASP.NET Core MVC .Net 8, Identity, 3-layer architecture, jQuery Ajax request, jQuery validation. Login successfully then Client-side redirection.

Login using ASP.NET Core MVC .Net 8, Identity, 3-layer architecture, Tag Helpers, form submission, jQuery Unobtrusive validation. Login successfully then Server-side redirection.

Practicing uses of: Abstraction, Encapsulation, Polymorphism and Inheritance. Interfaces, Inheritance between Interfaces. UML analysis and design. 3 layer architecture. Wrapper classes. Java classes: OBJECT, Scanner, Map, SimpleDateFormat, TreeMap, ArrayList and much more. This was an interesting project.

This project is a desktop application developed as a portfolio piece to demonstrate proficiency in **Java Desktop Development**. It focuses on the practical application of software engineering fundamentals, such as **3-layer architecture**, **DAO patterns**, and **OOP principles**.

Code base web application using Asp.Net Core MVC .NET 8, Identity, jQuery, 3 layers.

A demo application implemented in both 3-Layer and Hexagonal architectures.

A coding project aiming to design a 3-layer architecture CDSS

Working with APIs and 3-layers structures

Degrey Shop with ASP.NET and NextJs

Showcase of a 3 layer application with Python incl. Flask and PyTorch

Simple library management application written in C# with 3 layer pattern

Graph-based social network messaging service, powered by Neo4J. Developed for DevChallenge Backend 2022 competition

A course work project using Java core and aiming to partially simulate how does Hibernate work internally.

A straightforward E-Shop App written in Java using Spring and Vaadin. It follows a 3-layer architecture.

A complete Gym Management System built with ASP.NET Core MVC (.NET 9). Features role-based access, member & trainer management, plans, memberships, sessions, scheduling, and full 3-layer architecture.

Beautiful mobile application that gives you back ownership and insights into your data from social platforms.

Deep learning CNN model for pneumonia classification in chest X-rays. Optimized 3-layer architecture achieves 93.33% recall and 84.78% accuracy. Resource-efficient training (80% CPU), 75MB model, sub-2s inference. Live demo deployed on Streamlit with professional medical interface.