Ahmed H. Profile | Freelancer

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$35 USD / час

new cairo,

$35 USD / час

Сейчас здесь 12:43 PM

На сайте с января 2, 2019

1 Рекомендация

Ahmed H.

@amokhtar70

5,0

(18 отзывов(-а))

4,4

4,4

$35 USD / час

new cairo,

$35 USD / час

100 %

Завершенных работ

100 %

В рамках бюджета

100 %

Своевременно

38 %

Рейтинг повторного найма

Excel VBA, Macros, Google Apps Script, PowerShell

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.

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Элементы портфолио

Udacity Data Analysis Professional Nanodegree

Udacity Data Analysis Professional Nanodegree

Certified Quality Inspector - Institute of Quality Management
The American University in Cairo, Egypt

Certified Quality Inspector

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

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

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5,0

$30,00 USD

Modify excel sheet 2

Great at excell and macros. Able to figure out complex conditional macros. Very good communication. Works on only your project once hired. I will hire again.

Data Processing

B

Joseph U.

@bidmyforexmq4

•

20 дней назад

5,0

€220,00 EUR

Thanks you, great work.

+ еще 1

G

Petre V.

@Globalmarketit

•

25 дней назад

5,0

€150,00 EUR

Hist Sort and others

Thanks again for helping me out.

+ еще 1

G

Petre V.

@Globalmarketit

•

1 месяц назад

5,0

€100,00 EUR

Add more insights

Second time I work with Ahmed and once again perfect quality work, on time, and on budget. Will repeat

+ еще 1

H

Hector M.

@Hector4862

•

1 месяц назад

5,0

€175,00 EUR

Thanks you, really professional freelancer.

+ еще 1

G

Petre V.

@Globalmarketit

•

1 месяц назад

Опыт работы

Company

мая 2019 - Настоящее время

* Direct and monitor information technology capabilities to ensure the delivery of effective value creation of IT investments to support business goals.

Company

авг. 2015 - мая 2019 (3 года, 9 месяцев)

* 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.

Company

янв. 2010 - июл. 2015 (5 лет, 6 месяцев)

* Managing the audit of existing IT systems to ensure compliance with IT security policies and standards.

Образование

Certified Quality Inspector - Institute of Quality Management

The American University in Cairo,

Egypt

2011 - 2012

(1 год)

Bachelor of Engineering – Computer & Automatic Control Systems

Ain Shams University,

Egypt

1988 - 1993

(5 лет)

Квалификация

Udacity

2021

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

Udacity

2021

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

PeopleCert - AXELOS

2021

* 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.

Свяжитесь с Ahmed H. по поводу вашей работы

Авторизуйтесь для обсуждения любых деталей в чате.

Верификация

Предпочтительный фрилансер

Личность подтверждена

Метод оплаты верифицирован

Номер телефона верифицирован

Электронный адрес верифицирован

Связано с Facebook

Топ-навыки

13

10

9

Google Spreadsheets

7

6

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