https://github.com/harrystaley/open-source-data-science-degree-python
A fully curated, open-source Data Science curriculum focused on Python. Includes top-tier university courses (MIT, Stanford, Princeton) covering essential topics in computer science, data analysis, machine learning, and statistics — everything you need to build a solid foundation in Data Science, 100% free.
https://github.com/harrystaley/open-source-data-science-degree-python
data data-science dataanalysis datasci ds open open-source py python python3 science source statistics
Last synced: 6 months ago
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A fully curated, open-source Data Science curriculum focused on Python. Includes top-tier university courses (MIT, Stanford, Princeton) covering essential topics in computer science, data analysis, machine learning, and statistics — everything you need to build a solid foundation in Data Science, 100% free.
- Host: GitHub
- URL: https://github.com/harrystaley/open-source-data-science-degree-python
- Owner: harrystaley
- Created: 2022-03-27T16:25:43.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2025-04-12T09:11:21.000Z (6 months ago)
- Last Synced: 2025-04-13T09:19:02.529Z (6 months ago)
- Topics: data, data-science, dataanalysis, datasci, ds, open, open-source, py, python, python3, science, source, statistics
- Homepage:
- Size: 40 KB
- Stars: 15
- Watchers: 2
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Open-Source Data Science Degree - Python
This repository hosts a fully curated, open-source Data Science curriculum focused on Python. It includes top-tier university courses from MIT, Stanford, Princeton, and more, covering essential topics in computer science, data analysis, machine learning, and statistics. This repository provides everything you need to build a solid foundation in Data Science, and it's 100% free.
## Topics
- Data Science
- Open-Source
- Data Analysis
- Machine Learning
- Statistics
- Python
## Setup and Installation
To get started with this curriculum, you need to have Python installed on your computer. We recommend using Python 3.7 or later. You can download Python from [here](https://www.python.org/downloads/).
After installing Python, you will need to install some additional libraries. You can install these libraries using pip, which is a package manager for Python. Open your terminal and run the following command:
```bash
pip install numpy pandas matplotlib seaborn scikit-learn jupyterlab
```
This will install all the necessary libraries for data analysis and machine learning.
## Usage
Once you've installed Python and the necessary libraries, you can start exploring the courses and materials in this repository. Each course has its own folder with all the necessary materials and assignments.
For example, to start the course on Machine Learning from Stanford, navigate to the `machine_learning_stanford` directory and start the Jupyter notebook:
```bash
cd machine_learning_stanford
jupyter lab
```
## Contributing
We welcome contributions to this project! If you have a course or resource you'd like to add, please follow these steps:
1. Fork this repository.
2. Create a new branch in your forked repository.
3. Add your changes to the new branch.
4. Submit a pull request to this repository with a detailed explanation of the changes.
Please make sure your changes are in line with the project's overall goal and that they don't duplicate existing content.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.