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Ahmed H.

@amokhtar70

annual-level-two.svg
5,0
72
6,0
6,0
100%

Excel VBA, Macros, Google Apps Script, PowerShell

$40 USD / Time
・
Flag for
Egypt (2:57 PM)
・
Tilmeldt januar 2, 2019
$40 USD / Time
・
Hello, I am Ahmed Mokhtar Hassanein. • Engineer with a bachelor’s degree in Computer & Automatic Control Systems. • Excellent Excel VBA, Macros, and Formulas. • Excellent Google Sheets and Google Apps Script. • Excellent PowerShell scripting skills. • Data Analytics using Python, NumPy, Pandas, and Matplotlib. • Over 25 years’ experience supporting systems and users in the information technology field. • ITIL4 Managing professional. • Managed several implementations of network infrastructure, virtualization, domain controllers, application servers, network security, … etc. • Conducted tens of information systems audits and vulnerability assessments.
Verifikationer
Til tiden
100 %
Indenfor budgettet
100 %
Accept andel
97 %
Genansættelse andel
16 %
Freelancer Excel Experts Egypt
Se alle Excel Experts i Egypt

Portfolio-mappe

Portfolio-mappe

9511897
Udacity Data Analysis Professional Nanodegree
Udacity Data Analysis Professional Nanodegree
9502302
Certified Quality Inspector - Institute of Quality Management The American University in Cairo, Egypt
Certified Quality Inspector
9502216
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
9502197
ITIL 4 Managing Professional (ITIL MP) is a stream of four modules that are part of ITIL 4, the next evolution of ITIL. The four modules are: ITIL 4 Specialist Create, Deliver and Support ITIL 4 Specialist Drive Stakeholder Value ITIL 4 Specialist High-velocity IT ITIL 4 Strategist Direct, Plan and Improve. ITIL 4 MP has been created for IT practitioners working within technology and digital teams across businesses. The Managing Professional (MP) stream provides practical and technical knowledge about how to run successful IT enabled services, teams and workflows. ITIL® is a registered trade mark of AXELOS Limited.
ITIL4 Managing Professional
9511897
Udacity Data Analysis Professional Nanodegree
Udacity Data Analysis Professional Nanodegree
9502302
Certified Quality Inspector - Institute of Quality Management The American University in Cairo, Egypt
Certified Quality Inspector
9502216
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
In this project we'll be analyzing data associated with 'Medical Appointment No Shows'. 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. We are going to investigate the dataset in hand to fid answers for the following questions: 1- Research Q1: What is the influence of gender on showing-up to appointments? 2- Research Q2: Does age groups influence on showing-up to appointments? 3- Research Q3: Does sms received raise the chance of patients showing up for their scheduled appointment?
Data analysis of 'Medical Appointment No Shows' Dataset
9502197
ITIL 4 Managing Professional (ITIL MP) is a stream of four modules that are part of ITIL 4, the next evolution of ITIL. The four modules are: ITIL 4 Specialist Create, Deliver and Support ITIL 4 Specialist Drive Stakeholder Value ITIL 4 Specialist High-velocity IT ITIL 4 Strategist Direct, Plan and Improve. ITIL 4 MP has been created for IT practitioners working within technology and digital teams across businesses. The Managing Professional (MP) stream provides practical and technical knowledge about how to run successful IT enabled services, teams and workflows. ITIL® is a registered trade mark of AXELOS Limited.
ITIL4 Managing Professional
Ændringer gemt
5.0 · 72 Reviews
Bedømmelser
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Processing of Article Data from SUMITOMO • €220 EUR
Excellent cooperation! The solution is perfect and makes my work much easier. Thank you very much!
Florian M.
@florianbkw
•
Flag for
Kaarst, Germany
•
10 dage siden
Del
O
Excel Contract Management Sheet Tweaks • $80 USD
Ahmed is capable and professional, consistently going the extra mile by calling and providing updates to ensure the client receives exactly what they need. He offers solutions and explains them clearly. I highly recommend working with him.
Oscar Collie C.
@ocollie
•
Flag for
Miami Gardens, United States
•
18 dage siden
Del
O
Rearrange columns and update corresponding code • $30 USD
I am very pleased with his expert knowledge, work ethic, follow-ups, and updates. He consistently communicates to ensure he fully understands customer requirements, which helps save valuable time.
Oscar Collie C.
@ocollie
•
Flag for
Miami Gardens, United States
•
23 dage siden
Del
Brug Avatar.
Clean and import data • €280 EUR
Ahmed always delivers great work. He is punctual, reliable and exceeds expectations. I would recommend him at any time.
Florian M.
@florianbkw
•
Flag for
Kaarst, Germany
•
1 måned siden
Del
Brug Avatar.
Google Sheets Vacation Tracker & Dashboard • $350 USD
الشبخ احمد مبدع في الاقتراحات وتنوير الفكر للعملاء ومتعاون جداً ?
Ali B.
@alisbaharoon
•
Flag for
Jeddah, Saudi Arabia
•
2 måneder siden
Del
Erfaring
Company
jan., 2010 - Til stede
•
14 år, 10 måneder
IT Governance General Manager
maj, 2019 - Til stede
•
5 år, 6 måneder
* Direct and monitor information technology capabilities to ensure the delivery of effective value creation of IT investments to support business goals.
ICT QA / Security & Logistics General Manager
aug., 2015 - maj, 2019
•
3 år, 9 måneder
* Develop and maintain IT security documents including policies and processes in accordance with the latest security guidelines and alignment with business strategies. * Ensure effective monitoring and management of IT security threats, breaches, and major security incidents to protect business operations against violations. * Data quality management regarding accuracy, completeness, consistency, timeliness, uniqueness, and validity of data within company’s information systems.
Assistant General Manager for ICT Quality Assurance and Security
jan., 2010 - jul., 2015
•
5 år, 6 måneder
* Managing the audit of existing IT systems to ensure compliance with IT security policies and standards.
jan., 2010 - Til stede
•
14 år, 10 måneder
Uddannelse
The American University in Cairo
2011 - 2012
•
1 år
Certified Quality Inspector - Institute of Quality Management
Flag for
Egypt
2011 - 2012
•
1 år
Ain Shams University
1988 - 1993
•
5 år
Bachelor of Engineering – Computer & Automatic Control Systems
Flag for
Egypt
1988 - 1993
•
5 år
Kvalifikationer
Advanced Data Analysis Nanodegree
2021
Udacity
Udacity Advanced Data Analysis Nanodegree Certificate: * Advanced programming skills and ability to work with messy, complex datasets. * Manipulate and prepare data for analysis, and create visualizations for data exploration. * Tell a story with data. https://graduation.udacity.com/confirm/QMCMYQAN
2021
Data Analysis Professional Nanodegree
2021
Udacity
Udacity Data Analysis Professional Nanodegree Certificate: * Learn the data analysis process of questioning, wrangling, exploring, analyzing, and communicating data. * Use Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions. https://graduation.udacity.com/confirm/ADGAYCQX
2021
ITIL® 4 Managing Professional Transition Certificate
2021
PeopleCert - AXELOS
* ITIL 4 Managing Professional (ITIL MP) is a stream of four modules that are part of ITIL 4, the next evolution of ITIL. * ITIL 4 MP has been created for IT practitioners working within technology and digital teams across businesses. * The Managing Professional (MP) stream provides practical and technical knowledge about how to run successful IT enabled services, teams and workflows. ITIL® is a registered trade mark of AXELOS Limited.
2021
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