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$25 USD / hora
Bandeira do(a) EGYPT
al zaitoun, egypt
$25 USD / hora
Atualmente, está 10:05 AM aqui
Ingressou em março 13, 2014
0 Recomendações

Ebrahim A.

@Ibrahem404

 0,0 (0 avaliações)
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$25 USD / hora
Bandeira do(a) EGYPT
al zaitoun, egypt
$25 USD / hora
Não se aplica
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Não se aplica
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Não se aplica
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Data Analyst | Business Intelligence (BI) Analyst

Hi, I'm Ibrahem Shaker, and I am glad that you are here and see this. I have a bachelor of engineering with a major in Mechanical power engineering. I gain my experience from courses in my college and also online courses. I help businesses make better decisions through data analysis and visualizations. I have real technical skills, such as Python, pandas, Numpy, and tableau and always looking forward to learning new things and gaining more experience. My skills in fields: • Gather data from multiple sources, that being a local / cloud-based database, Excel / CSV files, web-scraped data, or using an API. • Statistical Analysis with Python / SQL. • Data Visualizations; building dashboards with Python, Power BI, and Tableau. I am pretty flexible concerning working hours, deadlines are sacred for me and I will always work to exceed your expectations. I sincerely wait for your kind reply.
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Portfólio

10254114
ver the past decade, bicycle-sharing systems have been growing in number and popularity in cities across the world. Bicycle-sharing systems allow users to rent bicycles on a very short-term basis for a price. This allows people to borrow a bike from point A and return it at point B, though they can also return it to the same location if they'd like to just go for a ride. Regardless, each bike can serve several users per day. Thanks to the rise in information technologies, it is easy for a user of the system to access a dock within the system to unlock or return bicycles. These technologies also provide a wealth of data that can be used to explore how these bike-sharing systems are used. In this project, you will use data provided by Motivate, a bike share system provider for many major cities in the United States, to uncover bike share usage patterns. You will compare the system usage between three large cities: Chicago, New York City, and Washington, DC.
BikeshareUS_project
ver the past decade, bicycle-sharing systems have been growing in number and popularity in cities across the world. Bicycle-sharing systems allow users to rent bicycles on a very short-term basis for a price. This allows people to borrow a bike from point A and return it at point B, though they can also return it to the same location if they'd like to just go for a ride. Regardless, each bike can serve several users per day. Thanks to the rise in information technologies, it is easy for a user of the system to access a dock within the system to unlock or return bicycles. These technologies also provide a wealth of data that can be used to explore how these bike-sharing systems are used. In this project, you will use data provided by Motivate, a bike share system provider for many major cities in the United States, to uncover bike share usage patterns. You will compare the system usage between three large cities: Chicago, New York City, and Washington, DC.
BikeshareUS_project
10254104
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
10254114
ver the past decade, bicycle-sharing systems have been growing in number and popularity in cities across the world. Bicycle-sharing systems allow users to rent bicycles on a very short-term basis for a price. This allows people to borrow a bike from point A and return it at point B, though they can also return it to the same location if they'd like to just go for a ride. Regardless, each bike can serve several users per day. Thanks to the rise in information technologies, it is easy for a user of the system to access a dock within the system to unlock or return bicycles. These technologies also provide a wealth of data that can be used to explore how these bike-sharing systems are used. In this project, you will use data provided by Motivate, a bike share system provider for many major cities in the United States, to uncover bike share usage patterns. You will compare the system usage between three large cities: Chicago, New York City, and Washington, DC.
BikeshareUS_project
ver the past decade, bicycle-sharing systems have been growing in number and popularity in cities across the world. Bicycle-sharing systems allow users to rent bicycles on a very short-term basis for a price. This allows people to borrow a bike from point A and return it at point B, though they can also return it to the same location if they'd like to just go for a ride. Regardless, each bike can serve several users per day. Thanks to the rise in information technologies, it is easy for a user of the system to access a dock within the system to unlock or return bicycles. These technologies also provide a wealth of data that can be used to explore how these bike-sharing systems are used. In this project, you will use data provided by Motivate, a bike share system provider for many major cities in the United States, to uncover bike share usage patterns. You will compare the system usage between three large cities: Chicago, New York City, and Washington, DC.
BikeshareUS_project
10254104
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.
TMDb movie data project

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Educação

Mechanical Power engineering bachelor degree

Cairo University, Egypt 2016 - 2022
(6 anos)

Qualificações

Data Analysis Professional Nanodegree Program

Udacity
2022
Credential ID 6KHLGRAL https://graduation.udacity.com/confirm/6KHLGRAL

Data Analysis challenger Nanodegree Program

Udacity
2021
Credential ID YUKU65L5

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Principais Habilidades

Python
SQL
MySQL
Microsoft Office
Tableau

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