This project explores factors that influence student performance by analyzing a publicly available dataset (e.g., from Kaggle). The aim is to preprocess, analyze, and derive insights to answer meaningful research questions about student performance.
- Data preprocessing and cleaning.
- Exploratory data analysis (EDA).
- Statistical analysis and modeling.
- Visualization of key insights.
To set up and run the project locally, follow these steps:
-
Clone the repository:
git clone https://github.com/KhoaUs/PDataScience.git cd PDataScience -
Install required dependencies:
pip install -r requirements.txt
-
Open the Jupyter Notebook:
jupyter notebook project.ipynb
- Follow the steps outlined in
project.ipynbto preprocess the data and perform analyses. - Modify the notebook as needed to address additional research questions.
| No. | Name | Student ID | |
|---|---|---|---|
| 1 | Vo Hung Khoa | 22127202 | vhkhoa22@clc.fitus.edu.vn |
| 2 | Vu Tuan Hung | 22127137 | vthung22@clc.fitus.edu.vn |
| 3 | Huynh Tan Dat | 22127059 | htdat222@clc.fitus.edu.vn |
All tasks for this project are managed in a shared Google Sheet:
The project repository is available on GitHub:
This project is for educational purposes only and is not intended for commercial use.