Project One: International Debt Statistics(World Bank Analysis)

It Analyzes global debt data to explore trends, key borrowers, and financial risks in developing countries.
A web application that visualizes and analyzes global debt data from the World Bank. Built with Jupyter Notebook and Power BI to analyze the data, it provides insights into trends, key borrowers, and financial risks in developing countries.
This project aims to analyze international debt statistics and delve into the key aspects of international debt statistics and the significance of such analysis in the global economy.
Features: Interactive charts, data filtering, country comparisons, and risk assessments.
Technologies: Python, Pandas, Matplotlib, Power BI.

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Project Two: E-Commerce Website (Only for Electronics)

This e-commerce website allows users to browse products, sign up or log in, add items to a shopping cart, and place orders. It features user authentication, product search and filtering, and a responsive interface for mobile and desktop users. Admins can manage products and view user activity.
The site is built using HTML, CSS, JavaScript, and optionally backend technologies like Node.js for data management. It includes a user-friendly interface with product categories, search functionality, and a secure checkout process.
Features: User authentication, product search, shopping cart, order management, admin dashboard.
Technologies: HTML, CSS, JavaScript, Java, SQL.

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Project Three: Currency Converter

A Currency Converter is a simple yet essential tool that enables users to convert an amount from one currency to another using real-time or updated exchange rates.
This project typically uses an external API (like exchangerate-api.com or exchangerate.host) to fetch live conversion rates.
Users select the source and target currencies, enter an amount, and get the converted value instantly. It's widely used in finance apps, e-commerce websites, and travel platforms.
Features: Real-time currency conversion, user-friendly interface, support for multiple currencies, and historical rate tracking.
Technologies: Python, Tkinter GUI Library, requests Module, and an external API for exchange rates.

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