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Schedule Interview NowMy name is Moaaz S. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Python, JavaScript, Data Analysis, Python Script, Linux, etc.. I hold a degree in . Some of the notable projects I’ve worked on include: Zerotty, PandaPrimes, yallakora_website_simple_Scraper, Medical Data Analysis, Video game data analsis, etc.. I am based in Alexandria, Egypt. I've successfully completed 6 projects while developing at Softaims.
I'm committed to continuous learning, always striving to stay current with the latest industry trends and technical methodologies. My work is driven by a genuine passion for solving complex, real-world challenges through creative and highly effective solutions. Through close collaboration with cross-functional teams, I've consistently helped businesses optimize critical processes, significantly improve user experiences, and build robust, scalable systems designed to last.
My professional philosophy is truly holistic: the goal isn't just to execute a task, but to deeply understand the project's broader business context. I place a high priority on user-centered design, maintaining rigorous quality standards, and directly achieving business goals—ensuring the solutions I build are technically sound and perfectly aligned with the client's vision. This rigorous approach is a hallmark of the development standards at Softaims.
Ultimately, my focus is on delivering measurable impact. I aim to contribute to impactful projects that directly help organizations grow and thrive in today’s highly competitive landscape. I look forward to continuing to drive success for clients as a key professional at Softaims.
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IBM Egypt
Zerotty is a terminal emulator project. It focuses on cross-compilation, native execution, and low-level design to achieve high speed and performance across various operating systems.
PandaPrime is a python module for dealing with primes easer and faster.
Simple python web scarping script made for yallakora web site. give it a date and it will return pandas data frame with the football matches in these day.
Overview: This graph summarizes the analysis of medical data, including adding an overweight column, normalizing the data, creating a chart of categorical features, cleaning the data, and creating a correlation matrix. Key Takeaways: BMI is used to determine if a person is overweight. Normalizing data makes it easier to compare variables. Cleaning data is important for accurate analysis. Correlation matrices can identify relationships between variables. Description: The graph shows the steps involved in analyzing medical data, including adding an overweight column based on BMI, normalizing the data, creating a chart of categorical features using seaborn's catplot(), cleaning the data, and creating a correlation matrix using seaborn's heatmap(). Implications: This graph highlights the importance of accurate data collection and cleaning in medical data analysis. It emphasizes the usefulness of visualizations in identifying patterns and relationships, which can ultimately be used to inform healthcare decisions and interventions.
A video game data analysis project involves collecting, processing, and interpreting data from various sources such as game logs and user feedback. The insights gained from this analysis can help game developers improve the gaming experience for players, identify potential areas for improvement, and drive revenue. As video games continue to grow in popularity, the demand for skilled data analysts in this field is expected to increase.
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