Welcome to the DataScience_Project_Pathrise repository! This project is part of the Pathrise application process and focuses on analyzing and predicting fellows' outcomes within the program. The project involves preprocessing data, conducting exploratory data analysis (EDA), creating a modeling pipeline, and presenting findings.

• Introduction
• Project Structure
• Getting Started
• Usage
• Results and Presentation
• Contributing
• License

The DataScience_Project_Pathrise assesses the ability to analyze and predict fellows' outcomes within the Pathrise program. The project covers data preprocessing, exploratory data analysis, building predictive models, and translating results into actionable recommendations for the company.

The project is organized into the following stages:

1. pathrise-Preprocessing.ipynb: This notebook contains the initial data preprocessing steps, including data cleaning, handling missing values, and feature engineering.

2. pathrise-EDA.ipynb: The exploratory data analysis notebook explores data patterns, distributions, and relationships, providing insights that inform the modeling process.

3. pathrise-ModelingPipeline.ipynb: This notebook outlines the development of a predictive modeling pipeline. It includes feature selection, model selection, hyperparameter tuning, and evaluation.

To explore the Pathrise Data Challenge project, follow these steps:

1. Clone this repository to your local machine:

git clone https://github.com/karrabi/DataScience_Project_Pathrise.git

2. Navigate to the project directory:

cd PathriseDataChallenge

3. Review the notebooks in each stage to understand the analysis process.

The project notebooks can be used as a guide to:

• Understand the data preprocessing steps necessary for analysis.
• Explore data patterns and relationships through EDA.
• Develop a modeling pipeline for predictive analysis.

Feel free to modify the code and analysis techniques according to your insights.

The final results and recommendations are documented in the pathrise_presentation.pptx presentation file. This presentation summarizes the findings, insights, and actionable suggestions based on the analysis.

Contributions are not expected for this project, as it's part of an assessment. However, if you discover any issues or have suggestions for improvements, please feel free to open an issue or provide feedback.

This project is provided as part of the Pathrise application process. All rights are reserved by Pathrise.

Explore the Pathrise Data Challenge Project to delve into the analysis and prediction of fellows' outcomes within the Pathrise program. Gain insights into the data science process and learn how to translate findings into actionable recommendations.

For any questions or further assistance, please contact [email protected].