Here is a graphical interactive Python tutorial to introduce beginners to data science methodology using Python
Github is static html
However, this jupyter notebook is interactive so to execute the code samples utilize binder link: 
I am using binder because it creates a multi-user Jupyter notebook server environment to run my interactive notebook which has a back end of three components:
The requirements3 file is required, it needs to be created in the root of the repository for Python 3 dependencies/packages that need to be installed at build time such as matplotlib, pandas
BinderHub is deterministically build docker images from a git repository + commit for who want to easily interact with computational environments that others have created. https://binderhub.readthedocs.io/en/latest/
repo2docker which is a tool that converts a code repository into a Docker image with an environment specified via dependency files (e.g., requirements.txt) http://repo2docker.readthedocs.io/en/latest/
JupyterHub, allows for a multi-user Jupyter notebook server as opposed to a locally hosted Jupyter notebook server(localhost:8888, 127.0.0.1:8888) which hosts user instances with a server in the cloud. We use a distribution of JupyterHub that runs on top of Kubernetes https://jupyterhub.readthedocs.io/en/latest/
For more information on utillizing mybinder for multi-user jupyter notebook hosting & jupyter notebooks in the future: https://jupyter-notebook.readthedocs.io/en/stable/public_server.html, https://jvns.ca/blog/2017/11/12/binder--an-awesome-tool-for-hosting-jupyter-notebooks/
You can also opt to host your own notebook server with Jupyterhub utilizing Helm, Kubernetes using Google Compute AWS or IBM Cloud if you choose in the future to create your own multi-user jupyter notebook hosting & jupyter notebooks https://zero-to-jupyterhub.readthedocs.io/en/latest/, https://blog.jupyter.org/binder-2-0-a-tech-guide-2017-fd40515a3a84