Mahazzani/BDAI_CapstoneProjectTwo_EducationalLandscape

Big Data and AI Engineering bootcamp 2nd capstone project. Using Big Data Tools to predict the probability of university enrollment for Egypt's High School students. # Educational Landscape Project As part of the Big Data and AI Engineering Onsite Bootcamp, we are asked to deliver a solution for the MENA market that can be solved by Big Data and AI tools. The project has to have an impact and deliver a solution for a real-world problem using MENA datasets. Table of Contents Project Overview Business Objective Methods Used Technologies Dataset Overview Preprocessing Overview Visualization Modeling Results Contributing Members Contact Acknowledgments ## ## Project Overview This is the overview of the project's structure and files for easier navigation. ``` ├── README.md ├── Deserts_Dashboard.pdf ├── presentation.pdf ├── Notebooks │ ├── CapstoneProject2_Preprocessing_Notebook.ipynb | ├── CapstoneProject2_EDA_Notebook.zip │ └── CapstoneProject2_ML_Notebook.ipynb └── Datasets (too big to be uploaded) ├── High_School_Public_Results_2022_EG_both_attempts.csv (original dataset) └── capstone_project2_preprocessed_eng.csv (output of the pre-preprocessing notebook: used for the EDA, Dashboard, and Machine Learning models) ``` ( back to top ) ## Business Objective The goal of this project is to forecast if a student can enroll in one of the public institutions in Egypt based on his current major and a few extracted attributes using data from a third-year secondary school dataset that was web scraped from the standardized tests in Egypt. ### Methods Used * Preprocessing * Feature Engineering * Feature Selection * Labeling and classifying the data * Exploratory Data Analysis * Data Visualization * Machine Learning * Oversampling ### Technologies * Python, Jupyter * Pandas * Plotly * Power BI * Pig (Big Data tool) * PySpark Machine Learning (Big Data tool) ( back to top ) ## Dataset Overview This dataset provides Egyptian student’s public results information. Including the student’s unique desk identifier number during the exam (this is unique for all students across Egypt), their gender and school name, the adm …