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$10 USD / ora
Bandiera: EGYPT
giza, egypt, egypt
$10 USD / ora
Attualmente sono le 11:17 PM qui
Registrato il luglio 1, 2017
0 Consigli

Amr M.

@EngAmr93

annual-level-two.svg 5,0 (4 valutazioni)
2,1
2,1
100%
100%
$10 USD / ora
Bandiera: EGYPT
giza, egypt, egypt
$10 USD / ora
100%
Lavori completati
100%
Nel budget
100%
Nei tempi previsti
20%
Tasso di riassunzione

Data Analyst | Process Control Engineer

My name is Amr. I studied Metallurgical and Materials Engineering. I worked as Quality Engineer at CIC (Cairo Inspection Company) and then as a Process Control Engineer at Ezz Steel. Following I started my work to be a data analyst in 2021 by participating in the initiative of the Ministry of Communication in Egypt. I was awarded 2 data analysis nano degrees from Udacity: • Data Analysis Professional Nano Degree. • Advanced Data Analysis Nano Degree. This encouraged me to learn more and more in my continuous learning journey. So, I spent a lot of time learning on 365 Data Science, Data Camp, and Coursera platforms, and reading the basic books for Data Science and statistical analysis. The skills that I acquired till now include: • R and its packages. • Minitab. • Microsoft Excel • Google Sheets • Python • Numpy • Pandas • Matplotlib • Seaborn • Probability • Statistics • R Programming • Microsft Power BI • Tableau This helped me land some jobs on Freelancer and Upwork platforms and got 5-star reviews.
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Contatta Amr M. per il tuo lavoro

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Portfolio

9987534
A UK-based online retail store has captured the sales data for different products for the period of one year (Nov 2016 to Dec 2017). The organization sells gifts primarily on the online platform. The customers who make a purchase consume directly for themselves. There are small businesses that buy in bulk and sell to other customers through the retail outlet channel. The job objective is to find significant customers for the business who make high purchases of their favorite products using clustering analysis in R studio and deliver an output via R Markdown.
Clustering analysis of E-commerce customers
A UK-based online retail store has captured the sales data for different products for the period of one year (Nov 2016 to Dec 2017). The organization sells gifts primarily on the online platform. The customers who make a purchase consume directly for themselves. There are small businesses that buy in bulk and sell to other customers through the retail outlet channel. The job objective is to find significant customers for the business who make high purchases of their favorite products using clustering analysis in R studio and deliver an output via R Markdown.
Clustering analysis of E-commerce customers
9942301
This Specialization has 7 courses and a Capstone project. The courses are: - Foundations: Data, Data, everywhere. - Ask questions to make data-driven decisions. - Prepare data for exploration. - Process data from dirty to clean. - Analyze data to answer questions. - Share data through the art of visualization. - Data analysis with R programming. The Skills acquired include: Data Aggregation | Data Analytics | Data Calculations | Data Cleaning | Data Ethics Data Visualization | Presentation | Problem Solving | R | Spreadsheets | SQL | Structured thinking
Google Data Analytics Certificate
9928089
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
9928053
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
9928049
Use Python code to get some statistics for 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. The dataset include: - Start Time (e.g., 2017-01-01 00:07:57) - End Time (e.g., 2017-01-01 00:20:53) - Trip Duration (in seconds - e.g., 776) - Start Station (e.g., Broadway & Barry Ave) - End Station (e.g., Sedgwick St & North Ave) - User Type (Subscriber or Customer) - Gender - Birth Year The statistics include: #1 Popular times of travel (i.e., occurs most often in the start time) #2 Popular stations and trip #3 Trip duration #4 User info
Python code to analyze Bikeshare data
Use Python code to get some statistics for 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. The dataset include: - Start Time (e.g., 2017-01-01 00:07:57) - End Time (e.g., 2017-01-01 00:20:53) - Trip Duration (in seconds - e.g., 776) - Start Station (e.g., Broadway & Barry Ave) - End Station (e.g., Sedgwick St & North Ave) - User Type (Subscriber or Customer) - Gender - Birth Year The statistics include: #1 Popular times of travel (i.e., occurs most often in the start time) #2 Popular stations and trip #3 Trip duration #4 User info
Python code to analyze Bikeshare data
9928042
The nanodegree from Udacity include 6 parts & 2 projects: The parts are: - Introduction to the Program - Introduction to Python - Introduction to Data Analysis - Data Wrangling - Digital Freelancing - Intro - Digital Freelancing - Pro The 3 projects are: 1. Analyzing the BikeShare data using python. 2. Wrangle and analyze WeRateDogs data by scrapping the data through Tweeter API then wrangle and clean the data using Pandas library (The cleaning process is documented and the issues found during the data cleaning is identified and corrected) then after cleaning the data is simply visualized to get some insights.
Data Analysis Professional Nano Degree
9987534
A UK-based online retail store has captured the sales data for different products for the period of one year (Nov 2016 to Dec 2017). The organization sells gifts primarily on the online platform. The customers who make a purchase consume directly for themselves. There are small businesses that buy in bulk and sell to other customers through the retail outlet channel. The job objective is to find significant customers for the business who make high purchases of their favorite products using clustering analysis in R studio and deliver an output via R Markdown.
Clustering analysis of E-commerce customers
A UK-based online retail store has captured the sales data for different products for the period of one year (Nov 2016 to Dec 2017). The organization sells gifts primarily on the online platform. The customers who make a purchase consume directly for themselves. There are small businesses that buy in bulk and sell to other customers through the retail outlet channel. The job objective is to find significant customers for the business who make high purchases of their favorite products using clustering analysis in R studio and deliver an output via R Markdown.
Clustering analysis of E-commerce customers
9942301
This Specialization has 7 courses and a Capstone project. The courses are: - Foundations: Data, Data, everywhere. - Ask questions to make data-driven decisions. - Prepare data for exploration. - Process data from dirty to clean. - Analyze data to answer questions. - Share data through the art of visualization. - Data analysis with R programming. The Skills acquired include: Data Aggregation | Data Analytics | Data Calculations | Data Cleaning | Data Ethics Data Visualization | Presentation | Problem Solving | R | Spreadsheets | SQL | Structured thinking
Google Data Analytics Certificate
9928089
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
Business Analyst career track with 10 courses listed below: o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics
Business Analyst career track certificate
9928053
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
This report summarizes the steps of work during Udacity project on Data Wrangling. This is the 2nd technical project in the data analysis professional track sponsored by Egy FWD initiative. The project includes gathering data from different sources: 1. From a CSV file (Enhanced twitter archive file downloaded from the internet – sent by the account of “WeRateDogs”. They already have downloaded it from twitter archive. ) 2. By building a query using Twitter API. 3. Image Predictions File that predict dog images using neural networks that are fed to it from twitter archive file. The gathered data is about tweets from a Twitter account named “WeRateDogs”. This account uploads images of dogs and text that includes a rating. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent."
Wrangle and analyze data
9928049
Use Python code to get some statistics for 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. The dataset include: - Start Time (e.g., 2017-01-01 00:07:57) - End Time (e.g., 2017-01-01 00:20:53) - Trip Duration (in seconds - e.g., 776) - Start Station (e.g., Broadway & Barry Ave) - End Station (e.g., Sedgwick St & North Ave) - User Type (Subscriber or Customer) - Gender - Birth Year The statistics include: #1 Popular times of travel (i.e., occurs most often in the start time) #2 Popular stations and trip #3 Trip duration #4 User info
Python code to analyze Bikeshare data
Use Python code to get some statistics for 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. The dataset include: - Start Time (e.g., 2017-01-01 00:07:57) - End Time (e.g., 2017-01-01 00:20:53) - Trip Duration (in seconds - e.g., 776) - Start Station (e.g., Broadway & Barry Ave) - End Station (e.g., Sedgwick St & North Ave) - User Type (Subscriber or Customer) - Gender - Birth Year The statistics include: #1 Popular times of travel (i.e., occurs most often in the start time) #2 Popular stations and trip #3 Trip duration #4 User info
Python code to analyze Bikeshare data
9928042
The nanodegree from Udacity include 6 parts & 2 projects: The parts are: - Introduction to the Program - Introduction to Python - Introduction to Data Analysis - Data Wrangling - Digital Freelancing - Intro - Digital Freelancing - Pro The 3 projects are: 1. Analyzing the BikeShare data using python. 2. Wrangle and analyze WeRateDogs data by scrapping the data through Tweeter API then wrangle and clean the data using Pandas library (The cleaning process is documented and the issues found during the data cleaning is identified and corrected) then after cleaning the data is simply visualized to get some insights.
Data Analysis Professional Nano Degree

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5,0
$50,00 USD
Project for Amr M. -- 3
always on time and the work is always well done as well.
Data Processing
Excel
Statistics
R Programming Language
+ 1 altro
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Bandiera: Mahra A.
@mhrals
•
2 anni fa
5,0
$20,00 USD
Project for Amr M. -- 2
Everything delivered on time and was done perfectly.
Data Processing
Excel
Statistics
R Programming Language
+ 1 altro
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Bandiera: Mahra A.
@mhrals
•
2 anni fa
5,0
$15,00 USD
Project for Amr M.
one of the best freelancers , he has done the project on time and was done perfectly.
Data Processing
Excel
Statistics
R Programming Language
+ 1 altro
M
Bandiera: Mahra A.
@mhrals
•
2 anni fa
5,0
$15,00 USD
Data Science with R programming + assessment
deleived the work in time and was done perfectly , good comunication and fast replies , will defenitely work with him again.
Data Processing
Excel
Statistics
R Programming Language
Statistical Analysis
M
Bandiera: Mahra A.
@mhrals
•
2 anni fa

Esperienza

Process Control Engineer

EZZ Flat Steel Company
ott 2017 - Attualmente
To ensure that work instructions is applied. To analyse the production database for control and improvement.

Freelancer Data Analyst

Freelancer
mar 2022 - Attualmente
Use the data analytics skills acquired from my nano degrees in Udacity and Google Data analytics program to make statistical analysis, business analysis, and more using SQL, spreadsheets, Python, and R programming.

Quality Control Engineer

CIC (Cairo Inspection Company)
ott 2016 - lug 2017 (9 mesi, 1 giorno)
To prepare the devices, make inspection plans, perform inspections on welds and metallic structures, and report the results.

Formazione

Bachelors degree in Metallurgical and Materials Engineering.

Suez Canal University, Egypt 2011 - 2016
(5 anni)

Certificati

Advanced Data Analysis Nano Degree

Udacity
2021
The program contains: - Python Programming. Here I use pandas and matplotlib libraries to analyze CO2 emissions data. - Statistics. - Probability. - A/B testing project. - Data Visualization using matplotlib and seaborn libraries.

Business Analyst career track program

365 Data Science
2021
The track consists of 10 courses (3 of them are elective and 7 are mandatory): o Introduction to Data and Data Science o Data Literacy o Data Strategy o Introduction to Excel o Data Analysis with Excel Pivot tables o Advanced Microsoft Excel o Statistics o The Complete Data Visualization Course with Python, R, Tableau, and Excel o Introduction to R programming o Mathematics

Excel Power Tools for Data Analysis

Macquarie University on Coursera
2021
The course illustrates the Power Query and Power Pivot tools in excel and ended with a dashboard creation in Microsoft Power BI. Skill include Power Query | Power Pivot | M-Language | DAX Language | Power BI.

Contatta Amr M. per il tuo lavoro

Accedi per discutere i dettagli via chat.

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Certificazioni

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Competenze principali

Data Processing 4
Excel 4
Statistics 4
R Programming Language 4
Statistical Analysis 4

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