Freelancer logotip
Prijava Vpis
Objavi projekt
RAZIŠČI
Android
Copywriting
Data Entry
Python
Training
Fotografija naslovnice profila
ne sledite
Napaka pri sledenju uporabnika.
Ta uporabnik drugim uporabnikom ne dovoli, da mu sledijo.
Temu uporabniku že sledite.
Vaš paket članstva omogoča samo 0 sledenj. Nadgradite tukaj.
Sledenje je bilo uspešno preklicano
Napaka pri preklicu sledenja uporabnika.
Uspešno ste priporočili
Napaka pri priporočanju uporabnika.
Nekaj je šlo narobe. Osvežite stran in poskusite znova.
E-naslov uspešno verificiran.
Avatar uporabnika

Omayma Ali A.

@engmim201087

0,0
0
0,0
0,0
0%

Computer Software, Data Analyst Engineer

$7 USD/uro
・
Zastava
Egypt (4:49 pop.)
・
Pridružen(a) od april 4, 2018
$7 USD/uro
・
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.
Verifikacije
Freelancer Python Developers Egypt
Glej vse Python Developers v Egypt

Portfelj

Portfelj

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
Spremembe so bile shranjene
0.0 · 0 Reviews
Ocene
Tukaj ni nobenih ocen!
Izkušnje
MicroController programmer
jan., 2011 - apr., 2012
•
1 leto, 2 meseca
Egy tronix
jan., 2011 - apr., 2012
•
1 leto, 2 meseca
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 leto, 2 meseca
Izobrazba
Al-Azhar University
2005 - 2010
•
5 let
Bachelor's degree - Computer and System Engineering
Zastava
Egypt
2005 - 2010
•
5 let
Kvalifikacije
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
Vabilo uspešno poslano!
Hvala! Po e-pošti smo vam poslali povezavo za prevzem brezplačnega dobropisa.
Pri pošiljanju vašega e-sporočila je šlo nekaj narobe. Poskusite znova.
Freelancer logotip Slovenia / Slovenščina
Pomoč & Podpora

Freelancer

KategorijeProjektiNatečajiFreelancerjiPodjetjaInovacijski izziviRazvoj z UIČlanstvoProgram prednostnih freelancerjevProjektno vodenjeLokalna delaPhoto AnywhereIzložbaAPI za razvijalceVerificirajte seNamizna aplikacija

O tem

O nasKako delujeVarnostVlagateljiZemljevid spletiščaZgodbeNoviceEkipaNagradeIzjave za javnostKariere

Pogoji

Politika zasebnostiPogojiPolitika o avtorskih pravicahKodeks ravnanjaProvizije in stroški

Partnerji

Escrow.comLoadshiftWarrior Forum

Aplikacije

Logotip Apple App StoreGoogle play logotip
Kopiranje v odložišče ni uspelo, poskusite znova po spremembi vaših dovoljenj.
Skopirano v odložišče.

Registrirani uporabniki

Skupaj objavljenih del

Freelancer ® is a registered Trademark of Freelancer Technology Pty Limited (ACN 142 189 759)

Copyright © 2025 Freelancer Technology Pty Limited (ACN 142 189 759)