Jupyter
The Jupyter service is a centrally hosted, browser-based platform for interactive programming, data analysis and scientific work. The Center for Information and Media Technologies (ZIM) provides a specially adapted JupyterHub for this purpose, which enables uncomplicated access to various JupyterLab environments.
Which JupyterLab environments are provided?
- Basic Python Environment: Minimalist environment for basic Python development.
- Scientific Python Environment: Scientific environment with popular packages from the Python ecosystem.
- TensorFlow environment: Specialized tools for machine learning with TensorFlow and deep learning packages.
- Pytorch environment: Specialized machine learning tools with Pytorch and deep learning packages.
- Julia environment: Designed for development with Julia, including popular packages and Julia kernel.
- R environment: Support for R, including popular packages and R kernel.
- Datascience environment: Designed for data science, with popular scientific Python packages.
- UPB_all environment: Combination of all the above environments in a single JupyterLab environment.
What are the access requirements?
- Authentication takes place via the central university account after prior service activation in the service portal.
- The service is used via a browser, so no further installation or configuration is required.
Special adaptations for teaching:
The JupyterHub has been expanded to include the Grader service especially for teaching:
Advantages for teachers
- Automated assessment of programming tasks
- Course management system for the administration of:
- Participants
- assignments
- submissions
- assessments
Advantages for students
- Direct feedback on programming tasks
- Uniform working environment for all course participants
- Automatic code review
- Clear progress indicator
Where can I get support and help?
For questions or technical problems:
- E-mail: zim@uni-paderborn.de
- Documentation: ZIM HelpWiki article on Jupyter