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Amr Kamil Abdelhalim A.

@amrkamil

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Data Analyst

$10 USD / Hour
・
Flag of
Egypt (4:59 AM)
・
Joined on April 26, 2011
$10 USD / Hour
・
MS Excel | SQL | Tableau | Python | R I’m a passionate Data Analyst who loves to dive into data & grab the interesting story it tells to help companies make effective data-driven decisions. My natural analytical and problem solving, leadership & project management skills were highly crafted through civil engineering study & work experience since 2009. My resilience, self discipline & commitment were sharpened while founding & maintaining my own successful construction business since 2014. While understanding people deeply & having the best communication possible with them came from working as a professional soft skills trainer since 2008. I believe that good attitude & personal skills are more rare than good technical skills & are much harder to be earned & I can promise you both. Technical Skills: - Data Analysis / Data Analytics - Data Cleansing - Data Wrangling - Visualization - MS Excel - SQL (BigQuery) - Tableau - Python (Pandas/NumPy/ Matplotlib) - R
Verifications
Freelancer Python Developers Egypt
See all Python Developers in Egypt

Portfolio

Portfolio

10869584
Role I was the data analyst responsible for the whole project Project goal This dataset collects information from 100k medical appointments in Brazil and is focused on the question of whether or not patients show up for their appointment. A number of characteristics about the patient are included in each row. I needed to answer this questions: What factors are important for us to know in order to predict if a patient will show up for their scheduled appointment? Conclusion From the analysis, we can see that patients who are males, with an appointment date on late weekdays & away from April & May, and live in some known areas tend to show more. Knowing that additional research should be conducted regarding the effect of sms received & transportation on No Show patients. This conclusion is limited to patients within investigated neighborhoods mentioned in the data. More research should be done for different world areas.
No-Show Medical Appointments Analysis
10869571
Conclusion: After analyzing 5. Millions trip records from the company data, I had these recommendations: - Initiating a “Summer Membership” for casual riders. - Marketing efforts shall be distributed between: - summer campaigns targeting casual riders to buy “Membership”. - campaigns on the rest of year to convert the regular casual riders into annual members.
Bike-Share Business Analysis
10869562
Role Data Analyst responsible for conducting the case analysis. Project goal Bike-Share Business Analysis: A ride-share company needed to understand the behavior of their "annual members" & casual riders" to decide where the company should focus its marketing efforts and to confirm whether it is a good idea to put efforts in converting “casual riders” to “annual members”.
Bike-Share Business Analysis
10855002
No-Show Medical Appointments Analysis
10854994
Bike-Share Business Analysis
10869584
Role I was the data analyst responsible for the whole project Project goal This dataset collects information from 100k medical appointments in Brazil and is focused on the question of whether or not patients show up for their appointment. A number of characteristics about the patient are included in each row. I needed to answer this questions: What factors are important for us to know in order to predict if a patient will show up for their scheduled appointment? Conclusion From the analysis, we can see that patients who are males, with an appointment date on late weekdays & away from April & May, and live in some known areas tend to show more. Knowing that additional research should be conducted regarding the effect of sms received & transportation on No Show patients. This conclusion is limited to patients within investigated neighborhoods mentioned in the data. More research should be done for different world areas.
No-Show Medical Appointments Analysis
10869571
Conclusion: After analyzing 5. Millions trip records from the company data, I had these recommendations: - Initiating a “Summer Membership” for casual riders. - Marketing efforts shall be distributed between: - summer campaigns targeting casual riders to buy “Membership”. - campaigns on the rest of year to convert the regular casual riders into annual members.
Bike-Share Business Analysis
10869562
Role Data Analyst responsible for conducting the case analysis. Project goal Bike-Share Business Analysis: A ride-share company needed to understand the behavior of their "annual members" & casual riders" to decide where the company should focus its marketing efforts and to confirm whether it is a good idea to put efforts in converting “casual riders” to “annual members”.
Bike-Share Business Analysis
10855002
No-Show Medical Appointments Analysis
10854994
Bike-Share Business Analysis
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Experience
Founder & Managing Director
May, 2014 - Present
•
10 years, 7 months
Comfort Spaces Constructions
May, 2014 - Present
•
10 years, 7 months
Managing small Construction Projects Design & Execution, including concrete structure, finishing & furnishing.
May, 2014 - Present
•
10 years, 7 months
Freelance
Jul, 2007 - Present
•
17 years, 5 months
Data Analyst
Nov, 2022 - Present
•
2 years, 1 month
I’m a passionate Data Analyst who loves to dive into data & grab the interesting story it tells to help companies make effective data-driven decisions. I'm proficient in using spreadsheet programs including MS Excel & Google Sheets. Also, I'm good at using Python, R, SQL & Tableau.
Trainer & Training Course Designer
Jul, 2007 - Present
•
17 years, 5 months
Designing and/or Delivering a wide range of soft skills training programs to audience ranging from corporate environments to university students.
Jul, 2007 - Present
•
17 years, 5 months
Education
Ain Shams University
2002 - 2009
•
7 years
Bachelor of Science (BS), Civil engineering
Flag of
Egypt
2002 - 2009
•
7 years
Qualifications
Google Data Analytics Professional Certificate
2022
Coursera
Gain an immersive understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job Learn key analytical skills (data cleaning, analysis, & visualization) and tools (spreadsheets, SQL, R programming, Tableau) Understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL and R programming Visualize and present data findings in dashboards, presentations and commonly used visualization platforms.
2022
Data Analysis Professional Nano Degree
2022
Udacity
Course Summary: Develop programs in Python Manipulate data using NumPy Load and process data using Pandas Use Anaconda to manage your programming environment Investigate a dataset using Python data analysis packages Perform the entire data analysis process on a dataset Gather data from multiple sources in a variety of formats Assess the quality and tidiness of data visually and programmatically Clean data using Python and Pandas
2022
Certifications
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