Choose your role

Nuvolos is designed for three primary audiences. Pick the path that matches your role to find your specific tutorials and how-to guides:

🎓 Instructors

Set up courses, distribute materials, manage assignments, and invite students.

• Tutorials

  • Your first course on Nuvolos

  • Running a data-heavy lab session

  • Reusing a course for the next term

• Guides

  • Join an organisation - accept an organisation-level invitation as Faculty or Manager so you can create your own courses.

  • Create a new course - set up a new course Space with name, description, and a starter Application.

  • Add teaching material - upload files into the Master Instance where you develop course content.

  • Structure your course - choose the Instance layout that matches how students will work.

  • Document your course - use README.md files and embedded videos to introduce the course on its overview page.

  • Invite students - send invitations so each student receives their own individual Instance.

  • Invite teaching assistants and co-instructors - invite colleagues as Space Administrators with full course management rights.

  • Distribute teaching material - push files, tables, or Applications from the Master Instance to every student.

  • Set up group projects - create per-group Instances in a separate group-work Space.

  • Configure course tools and resources - manage Applications and resources for the entire cohort.

  • GPU courses - enable GPU access, schedule lab sessions, or set up On-Demand GPU with Credit quotas.

  • Assignments, grading, and feedback - create, distribute, grade, and hand back Assignments.

  • Archiving your course - manage the course archival lifecycle and access student work after archival.

📖 Students

Join a course, start Applications, and use Snapshots to save your work.

• Tutorials

  • Your first Nuvolos session

  • Submitting your first assignment

  • Working on a group project

• Guides

  • Accept a course invitation - join a course by accepting the invitation email from your instructor.

  • Find your course materials - locate the files, datasets, and Applications your instructor has distributed to you.

  • Understand the course layout - learn the difference between your personal Instance and the Distributed Instance.

  • Use applications - start and stop Applications like JupyterLab, RStudio, or VS Code.

  • Work with files - upload, download, edit, and organise files in your Instance.

  • Complete and submit assignments - work on Assignments, hand them in, and review instructor feedback.

  • Save and recover work - take snapshots before major changes and restore previous states when needed.

  • Collaborate and use special resources - work in shared group Instances and use GPU access in your course.

  • Working with archived courses - access your work after a course is archived and restore from snapshots.

  • Leaving a course - remove yourself from a course while preserving your Instance and work.

🔬 Researchers

Create projects, manage data, run Applications, and collaborate with colleagues.

• Tutorials

  • Your first research project

  • From notebook to reproducible result

  • Reproducing a colleague's research project

• Guides

  • Join an organization - accept an organisation-level invitation as Faculty or Manager so you can create your own projects.

  • Create a research project - set up a new research Space with the right visibility for your work.

  • Join a research project - accept an invitation to an existing project as Space Administrator or Instance Editor.

  • Add material to the project - bring files, code, and data into your project from local uploads, Git, or external storage.

  • Create alternate approaches - branch off into new Instances for parallel experimentation.

  • Invite collaborators - invite co-authors as Space Administrators or single-Instance contributors as Instance Editors.

  • Invite an external reviewer - give a journal editor or reviewer an isolated copy of your work to inspect.

  • Run analyses and applications - create, start, and stop Applications for your research.

  • Set up a dataset - publish curated, vintaged data to a Dataset Space.

  • Import data - bring external data into Nuvolos via uploads, downloads, mounts, or data pipelines.

  • Database research workflow - Matlab & RStudio - query the Scientific Data Warehouse, analyse in Matlab or RStudio, and write results back.

  • GPU Computation - configure GPU sizes and install libraries for PyTorch, TensorFlow, or XGBoost.

  • Scale and automate - scale to HPC and automate workflows with the CLI or Python API.

  • Preserve and share results - export your project as a portable image and share snapshots with collaborators.