Back-end Developer
I am a Senior student in the faculty of computers and information Cairo university, with a strong background in backend development with Laravel, I bring academic experience in solid foundation and OOP. Currently working on the backend of Med Sync, a medical system encompassing both mobile app and website platforms. .
Skills
Experience
Education
Frontend Development encompasses HTML, CSS, JavaScript, and Bootstrap. Backend Development involves PHP, Laravel, and Django.
SDLC (Software Development Life Cycle) Testing: . OOP (Object-Oriented Programming): SOLID: SOLID is ans. Design Patterns
SQL, TSQL, SSIS, Querying and manipulating data stored in SQL Server databases Building complex data integration workflows to extract, transform, and load data
- Filtering the leads data.
- Contacting the leads to explain FriendyCar’s service and encourage them to converge.
- Support the new users via WhatsApp.
- Managing workshops' specialization from planning to production.
- Delivering workshops to participants.
- Recruiting and interviewing qualified participants.
- Developing and monitoring participants' learning curve and progress.
- Improving the technical skills of the participants.
- Preparing the participants to work on projects.
- Creating workshop materials and presentations.
- Photography and video making.
- Coverage for SCCI's sessions and events.
- Visual documentaries for SCCI.
- Managing SCCI's YouTube channel.
This project aims to develop a robust software solution for managing service providers.
In this project, we have implemented the SOLID principles, the Strategy pattern, and the Decorator design pattern.
We have built an API for each function using the Spring framework and Java,
which can be tested using Postman.
This project implements a data warehouse solution using the Olist E-Commerce store dataset.
The data is extracted from the source system, transformed using SSIS (SQL Server Integration Services),
and loaded into the destination database.
The project involves the creation of six dimensions and three fact tables in the destination database.
True-fake-news is a NLP model that aims to address the challenge of detecting and classifying news articles as true or fake. This project leverages machine learning techniques to build a model that can accurately predict the authenticity of news articles. By providing a reliable tool for news verification, we aim to combat misinformation and promote informed decision-making.
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