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-egy-estates

Web Scraping using scrapy to gather the real estate data from olx • Cleaning and analysis • Database (SQLite) • Machine learning model to predict the price of real estate with accuracy 90% • Frontend -backend (Django) • Development on AWS

ab-testing

Analyze A/B Test Results A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these. For this project, you will be working 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. Your 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. The data and the Jupyter Notebook, which are all of the files you need to complete the project, are provided for you in a downloadable zip file in the resources tab (as well as under "Supporting Materials" below). Note that portions of the notebook reference back to quizzes that are linked in this lesson to ensure you are on the right track. Although the quizzes in this lesson are not necessary to successfully complete the project (though they are helpful), all of the items on the Project Rubric must meet specifications to successfully complete the project.

artificial-intelligence-analyst

collage-web-page

Using Docker, and Docker compose to make a website with a small database and allow your machine to act like a server and accept HTTP requet

dashboard-for-sales-data-using-excel

# DASHBOARD-FOR-SALES-DATA-USING-EXCEL 1)Data cleansing with Power Query and Excel 2)Using pivot tables and Formulas to calculate results 3)Visualizing data with Pivot Charts and Excel Charts 4)Create a dashboard template using power point and combine everything into one that can tell a story 5)Tools Used {Excel formulas, Power Query, Pivot Tables, Developer Mode, Pivot Chart, Power point}

dashboard-with-excel

# DASHBOARD-FOR-BIG-FASHION-GROUP-USING-EXCEL 1)Data cleansing with Power Query and Excel 2)Using pivot tables and Formulas to calculate results 3)Visualizing data with Pivot Charts and Excel Charts 4)Create a dashboard 5)Tools Used {Excel formulas, Power Query, Pivot Tables, Developer Mode, Pivot Chart}

data-exploration-and-filteration

data-wrangle-and-visualization

Real-world data rarely comes clean. Using Python and its libraries, you will 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. You will document your wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations using Python (and its libraries) and/or SQL. The dataset that you will be wrangling (and analyzing and visualizing) is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. 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." WeRateDogs has over 4 million followers and has received international media coverage. WeRateDogs downloaded their Twitter archive and sent it to Udacity via email exclusively for you to use in this project. This archive contains basic tweet data (tweet ID, timestamp, text, etc.) for all 5000+ of their tweets as they stood on August 1, 2017. More on this soon. link : https://classroom.udacity.com/nanodegrees/nd002-mena-nfp2/parts/af4e9844-89bd-49ab-a05d-d47d167a24ba/modules/16455e0d-66fb-4506-a177-4ba45678e8db/lessons/a8085857-3e28-4fc7-aeb8-da64ccbc2e20/concepts/5e3db54a-1a5f-41a6-8e20-fd99f201861d

data_structures_and_algorithms

A git repository for Data Structures & Algorithms codes, illustrations and sheets solutions as explained in Data Structures & Algorithms course (02-24-00108) at the Faculty of Computing and Data Science, Alexandria University. It will be updated on regular basis.

database-for-real-clothes-store

lovecraft-austin-and-docker-

When a book has entered “the public domain,” its copyright has expired and the material now belongs to the general public. Not only does this mean that anybody can creatively reinvent that original work without paying a penny but also that this book is now free for anyone to read. Two of the books which entered the public domain are HP Lovecraft’s Beyond the Wall of Sleep, and Jane Austin’s Pride and Prejudice. Given both books (attached as links below), you are tasked to find common words between those two books. You should consider the following: Upper-cased and lower-cased words, Punctuation marks, Extra white spaces, The encoding of the files, e.g. utf-8, and Empty lines Write a Docker image to perform the previous analysis on both books, i.e. to find the common words. Make sure to write a clean, coherent code. You MUST submit the following: Your source codes (Java, Python, ...etc), Your Dockerfile, Necessary dependencies, Any asset for your image to be successfully built on other devices, and Pushing your image on hub.docker.com is a plus! HP Lovecraft’s Beyond the Wall of Sleep https://www.hplovecraft.com/writings/texts/fiction/bws.aspx Jane Austin’s Pride and Prejudice https://www.gutenberg.org/files/1342/1342-h/1342-h.htm

medical-data-appointments

This dataset collects information from 100k medical appointments in Brazil and is focused on the question of whether patients show up for their appointment. A number of characteristics about the patient are included in each row.

power-bi-dashboard

search-in-dictionary

software-engineering-pos-project

A POS (point of sale) system is a system that is used for your business that allows your business to accept payments from customers and keep track of sales.

widebot-task1

widebot-task2

widebot-task3

wuzzuf-time-data-visualization-