Tamer Abdelaty Ahmed
Data Analyst at Freelancing
Data Analytics at Udacity + ITIDA
Egypt
Hi, I'm Tamer Abdelaty Ahmed!
Data Analyst at Freelancing
Tamer is a Data Scientist & Engineer with over 6 years of experience in the IT field, specializing in data science and big data engineering. He has honed his skills in various technologies, including Python, Apache Airflow, R, NumPy, Spark SQL, SQL, PostgreSQL, Apache Cassandra, ETL, Mongo DB, Tableau, etc. Throughout his career, Tamer has worked on various projects with different focuses. His primary responsibilities are deeply rooted in the field of data science and big data engineering. They include managing and analyzing large datasets, developing and optimizing ETL processes, implementing data exploration techniques, and applying deep learning algorithms. His work also involves data collection and the use of computer vision in data analysis. With his extensive experience and diverse skill set, Tamer has proven to be a valuable asset in the data science and big data engineering field.
Experience
Freelancing
Data Scientist | Data Engineer
January 2018 - February 2024
Identifying relevant data sources for business needs Collecting structured and unstructured data Sourcing missing data and building ETL pipelines Organizing data into usable formats and implementing the appropriate data architecture solution Building predictive models Building machine learning algorithms
Seif Group
Data Analyst
January 2017 - December 2018
Conducting comprehensive data analysis to drive business decisions Collaborating with the team to define project objectives, set key performance metrics, and establish project approaches Presenting findings to stakeholders and team members to drive business strategies
Education
Artificial Intelligence
Udacity
Graduated in 2021
Certificates & Badges
No certificates or badges added
Projects
A Visual History of Nobel Prize Winners
•https://github.com/TamerAbdelatyAhmed/A-Visual-History-of-Nobel-Prize-WinnersDatacamp Data Science with Python Career Track.
The Nobel Prize is perhaps the world's most well known scientific award. Except for the honor, prestige and substantial prize money the recipient also gets a gold medal showing Alfred Nobel (1833 - 1896) who established the prize. Every year it's given to scientists and scholars in the categories chemistry, literature, physics, physiology or medicine, economics, and peace. The first Nobel Prize was handed out in 1901, and at that time the Prize was very Eurocentric and male-focused, but nowadays it's not biased in any way whatsoever. Surely. Right?
Analyzing Streaming Service Content in SQL.
•https://github.com/TamerAbdelatyAhmed/Analyzing-Streaming-Service-Content-in-SQLData Science | Data Analyst | SQL
I analyze the data in a SQL database and visualize the results.
To set up my integration,I create a PostgreSQL integration with the following credentials:
Integration Name: Streaming Codealong Hostname: workspacedemodb.datacamp.com Database: streaming Username: streaming_codealong Password: streaming_codealong
The GitHub History of the Scala Language.
•https://github.com/TamerAbdelatyAhmed/The-GitHub-History-of-the-Scala-LanguageDatacamp Data Scientist with Python Track.
Open source projects contain entire development histories, such as who made changes, the changes themselves, and code reviews. In this project, I have been challenged to read in, clean up, and visualize the real-world project repository of Scala that spans data from a version control system (Git) as well as a project hosting site (GitHub).
The Android App Market on Google Play.
•https://github.com/TamerAbdelatyAhmed/The-Android-App-Market-on-Google-PlayDatacamp Data Scientist with Python Career Track.
Mobile apps are everywhere. They are easy to create and can be lucrative. I did a comprehensive analysis of the Android app market by comparing over ten thousand apps in Google Play across different categories. I looked for insights in the data to devise strategies to drive growth and retention.
Investigating Netflix Movies and Guest Stars in The Office
•https://github.com/TamerAbdelatyAhmed/Investigating-Netflix-Movies-and-Guest-Stars-in-The-OfficeDatacamp Data Scientist with Python Career Track.
Netflix! What started in 1997 as a DVD rental service has since exploded into the largest entertainment/media company by market capitalization, boasting over 200 million subscribers as of January 2021. Given the large number of movies and series available on the platform, it is a perfect opportunity to flex our data manipulation skills and dive into the entertainment industry. Our friend has also been brushing up on their Python skills and has taken a first crack at a CSV file containing Netflix data. For their first order of business, they have been performing some analyses, and they believe that the average duration of movies has been declining.
Data Analyst, Statistics, Data Scientist and Machine Learning Specialist.
For this project, the goal is to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product. The goal is to work through this notebook to help the company understand if they should implement this new page, keep the old page, or perhaps run the experiment longer to make their decision.
Data Analyst, Statistics and Data Scientist.
I investigate a classic phenomenon from experimental psychology called the Stroop Effect. I learn a little bit about the experiment, create a hypothesis regarding the outcome of the task, then go through the task. I then look at some data collected from others who have performed the same task and will compute some statistics describing the results. Finally, I interpret the results in terms of my hypotheses.
Data Analyst.
In this project, I analyze a dataset and then communicate my findings about it. I use the Python libraries NumPy, pandas, and Matplotlib to make my analysis easier. five steps of investigation : Data Wrangling, Data Cleaning, Exploratory Data Analysis & visualizations, Conclusions, Communications.
Data Analyst & Python Developer.
I make use of Python to explore data related to bikeshare systems for three major bikeshare systems in the United States. I perform data wrangling to unify the format of data from the three systems and write code to compute descriptive statistics.
Explore Weather Trends.
•https://github.com/TamerAbdelatyAhmed/Tamer-Udacity-Exploring-Weather-TrendsData Analyst.
Exploring Weather Trends by using Reporting, Moving average, Microsoft excel, Pivot table, Data visualization, statistics, SQL. I analyze local and global temperature data and compare the temperature trends where I live to overall global temperature trends.
Query-a-Digital-Music-Store-Database.
•https://github.com/TamerAbdelatyAhmed/Query-a-Digital-Music-Store-Database.Business Analytics.
In this project, I query the Chinook Database. The Chinook Database holds information about a music store. For this project, I'm assisting the Chinook team with understanding the media in their store, their customers and employees, and their invoice information. The schema for the Chinook Database is provided below. I can see the columns that link tables together via the arrows.
Business Analytics.
In this project, I analyze a real dataset about current Udacity students across a number of programs, so it isn't perfect. It is a little messy (some things are input incorrectly, others are missing). I need to decide how to analyze the data and then communicate your findings about it. You will use spreadsheets to make your analysis easier (please do not analyze by hand; it will take forever!). Prepare with the descriptive statistics and spreadsheet lessons leading up to the project.
Data Analyst & R Developer.
I use R and apply exploratory data analysis techniques to explore relationships in one variable to multiple variables and to explore a selected data set for distributions, outliers, and anomalies.
Data Analyst.
Real-world data rarely comes clean. Using Python and its libraries, I gather data from a variety of sources and in a variety of formats, assess its quality and tidiness, then clean it. This is called data wrangling. I document my wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations using Python (and its libraries) and/or SQL.
Data Analyst.
I create a data visualization using Tableau that tells a story or highlights trends or patterns in a data set. My work should be a reflection of the theory and practice of data visualization, such as visual encodings, design principles, and effective communication.
Create a Medical Image Data Annotation Job.
•https://github.com/TamerAbdelatyAhmed/Create-a-Medical-Image-Data-Annotation-JobArtificial Intelligence.
In this project, you'll be designing a data annotation job using Appen's data annotation tools. You can learn more on their platform homepage. The goal of data annotation is to bring you from unstructured, unlabeled data, to a desired, labeled output. This platform will send the data to human annotators that can help transform unlabeled data.
Build a Model with Google AutoML
•https://github.com/TamerAbdelatyAhmed/Build-a-Model-with-Google-AutoMLArtificial Intelligence
In the previous project, you created the instructions needed to build a labeled dataset that distinguishes between healthy and pneumonia x-ray images. This dataset would eventually be used to build a product that helps doctors quickly identify cases of pneumonia in children. Remember that the goals of this product are to: help flag serious cases, quickly identify healthy cases, and, generally, act as a diagnostic aid for doctors. In this project I built the classification model that would serve as the backbone of this product. The Four Parts of the Project I trained four different models using four variants of the pneumonia dataset. Recall that the dataset contains childrens' chest x-ray images, and that they are classified into two classes, "normal" and "pneumonia". The following sections describe the steps you must take to create each model. I Created a binary classifier to detect pneumonia using chest x-rays We'll start by training a model simply using 100 images from the “normal” class and 100 images from the “pneumonia” class. I evaluated the following: Train/test split: How much data is used for training and how much is used for testing?
Create an AI Product Business Proposal.
•https://github.com/TamerAbdelatyAhmed/Create-an-AI-Product-Business-ProposalArtificial Intelligence.
In this project, you'll develop a business proposal for an AI product. There are several important aspects of product development you'll need to think about and describe, and they are exactly the topics we've covered in this course. Here, we'll walk through what should be included in the proposal. You'll also find instructions in the Capsone Project Starter File, linked at the bottom of the page. You need to answer the questions in this file to complete the project. This project is open-ended in that you can propose any product in any industry that you want! If you're stuck, feel free to think about and research one of the use cases we've already discussed in this course. As a tip, you may find that your strongest ideas come from business arenas you are interested in and may already know a lot about. The Business Goal You'll need to describe what the product is, and how it will provide value to the business. It's important in this section to describe exactly what the product will do and why/how this helps the business. Focus on linking the AI/ML task to business goals such as increasing revenue or customer happiness. Success Metrics You'll also need to describe how you'll know whether the product is successful. Think about measurable, predictive, comparable, and benchmarked metrics for business success. Data You should carefully consider how you will acquire the data to train your model, and issues that may arise during data collection. Important considerations include: buying data vs. collecting it, personally identifying information (PII) and data sensitivity, cost, and whether data will be continuously available or acquired in one large batch (and need to be refreshed). Model When thinking about how you will build the model, will you use an in-house data science team because none of the out of the box platforms have your use case, or because you want the ability to control a particular aspect of your mode.
Languages
Arabic
Native
English
Professional
Skills
Data
Data Analysis
Data Analytics
Data Analytics Developer
SQL
Python
Python Data
R Language
Excel
Tableau
Machine Learning
Machine Learning Algorithms
Data Science
Statistics
A/B Testing (Split Testing)
Hypothesis Testing
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