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Omayma Ali A.

@engmim201087

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Computer Software, Data Analyst Engineer

$7 USD / Time
・
Flag for
Egypt (12:17 AM)
・
Tilmeldt april 4, 2018
$7 USD / Time
・
Each time I learn new things about software engineer, I love it more than before. In my previous work on the KAS board, when I wrote the code to solve the problem in the elevator then test it, I was feeling proud and passionate to learn more in the world of programming. I'm a Computer and system engineer who graduated from the University of Al-Azhar, a fast self-learner, familiar with lots of programming languages(C - C++ - C# - Java), worked in EGYtronix company in programming Kas elevator board on Embedded systems using C language. Then, I decided to Delves more into web and Android applications. So I have learned Web Applications at Udacity using HTML5 & CSS3 & JavaScript. Also, studied Android applications at Udacity using Java. Now, I am learning data analysis at Udacity. I exceeded the challenger track and at the end of the professional track. I will complete the advanced and learn more about data in our world. I learned in Udacity working with Pandas, Numpy, Matplotlib Packages. Also, I worked on Atom, Jupyter Notebook. I can wrangle any data by ( gathering, assessing, cleaning ) it, then analyze it and answer any questions about this data and visualize the results to be more attractive to the human.
Verifikationer
Freelancer Python Developers Egypt
Se alle Python Developers i Egypt

Portfolio-mappe

Portfolio-mappe

7383020
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
7382898
I used Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. l wrote code to import the data and answer interesting questions about it by computing descriptive statistics. I also wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.
Explore US Bikeshare Data
I used Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. l wrote code to import the data and answer interesting questions about it by computing descriptive statistics. I also wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.
Explore US Bikeshare Data
I used Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. l wrote code to import the data and answer interesting questions about it by computing descriptive statistics. I also wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.
Explore US Bikeshare Data
I used Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. l wrote code to import the data and answer interesting questions about it by computing descriptive statistics. I also wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.
Explore US Bikeshare Data
7383020
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
The dataset that I wrangled and analyzed and visualized is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. WeRateDogs has over 4 million followers and has received international media coverage. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. I documented my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations.
WeRateDogs Twitter Account Data Analysis
7382898
I used Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. l wrote code to import the data and answer interesting questions about it by computing descriptive statistics. I also wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.
Explore US Bikeshare Data
I used Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. l wrote code to import the data and answer interesting questions about it by computing descriptive statistics. I also wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.
Explore US Bikeshare Data
I used Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. l wrote code to import the data and answer interesting questions about it by computing descriptive statistics. I also wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.
Explore US Bikeshare Data
I used Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. l wrote code to import the data and answer interesting questions about it by computing descriptive statistics. I also wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.
Explore US Bikeshare Data
Ændringer gemt
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Bedømmelser
Ingen anbefalinger at se her!
Erfaring
MicroController programmer
jan., 2011 - apr., 2012
•
1 år, 2 måneder
Egy tronix
jan., 2011 - apr., 2012
•
1 år, 2 måneder
I was responsible for : - Developing Kas elevator control board using C language. - Designing and developing device drivers. - Configuring and testing the Microcontroller. - Troubleshooting and debugging.
jan., 2011 - apr., 2012
•
1 år, 2 måneder
Uddannelse
Al-Azhar University
2005 - 2010
•
5 år
Bachelor's degree - Computer and System Engineering
Flag for
Egypt
2005 - 2010
•
5 år
Kvalifikationer
Data Analysis - Professional Track
2020
Udacity
I have learned the following : - Introduction to python which includes Data types and operators, Data Structures, Control Flow, Functions, Scripting, Numpy, Pandas. Its project was to Explore Bike share Data. - Introduction to Data Analysis which includes Anaconda, Jupyter Notebook, the data analysis process, and programming workflow for Data Analysis. - The Data Wrangling phases gathering, assessing, cleaning.
2020
Data analysis - Challenger Track
2020
Udacity
I have learned the following: - statistics. - spreadsheets. - business metrics. - freelancing.
2020
Android Development
2018
Udacity
I've learned the following : - Create and run android apps. - Create a layout for android using the Android Studio IDE. - Load Data from the Internet. - About the components that convert a list of data into visual UI elements (RecyclerView). - Intents. - The Application Lifecycle. - Content Providers provide an interface to share data and Consume it. - Run jobs in the background of an app, Create notifications, and schedule long-running background processes. - Add visual polish to the Apps.
2018
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