University of Bremen

60 University of Bremen - JupyterHub https://www.uni-bremen.de/en/zmml/jupyter Jupyter is a web-based application that combines executable code, text and multimedia in so-called Jupyternotebooks. With an interactive development environment, students can easily learn the basics of programming, data analysis or machine learning. en University of Bremen Fri, 06 Mar 2026 18:34:24 +0100 Fri, 06 Mar 2026 18:34:24 +0100 University of Bremen content-569537 Wed, 24 Sep 2025 11:48:43 +0200 Jupyter – Exploratory data analysis with code, multimedia content and interactive visualisation https://www.uni-bremen.de/en/zmml/jupyter#c569537 Jupyter is a web-based open source software. Users can connect, share and reuse multimedia content within the framework of a notebook: Text, images, videos, interactive content and the special basic feature of executable programming code in various programming languages such as Python, R or Java. These are good prerequisites for teaching programming skills and data literacy, the ability to understand, process, describe, interpret and discuss issues with the help of data. <h5>How you can reach JupyterHub at the University of Bremen&nbsp;</h5> Jupyter is available for use by all members of the University of Bremen <a class="externalLink" href="https://jupyter.uni-bremen.de/" target="_blank" title="Öffnet externen Link in neuem Fenster">https://jupyter.uni-bremen.de/</a> You can log in with your university login (Shibboleth).&nbsp; Further information can be found on this page or on the JupyterHub page. If you have any further questions, please contact the Jupyter team at the following email address <a class="mail" href="mailto:in" title="Öffnet ein Fenster zum Versenden der E-Mail">info@jupyter.uni-bremen.de</a> Content content-569543 Fri, 06 Mar 2026 11:56:22 +0100 Registration on JupyterHub https://www.uni-bremen.de/en/zmml/jupyter#c569543 Jupyter at the University of Bremen can be reached at&nbsp; <a class="externalLink" href="https://jupyter.uni-bremen.de" target="_blank" title="Opens external link in new window">https://jupyter.uni-bremen.de</a> On the JupyterHub homepage, click on the login button (1). You will then be redirected to the Single-Sign-On page of the Centre for Networks, ZfN (2).&nbsp; Log in here with your user name (2a) and password (2b). After clicking on "Login" (2c) you will land on the profile page of JupyterHub at the University of Bremen. Three standard profiles (3a) for the programming languages Python, R and Java are currently available here for you to try out. Please note the information on the respective versions and pre-installed packages and libraries of the profiles in the description.&nbsp; Some users make their profiles available to everyone; these can be found in the accordion section "Public profiles" (3b).&nbsp; If you have created your own profiles, you will also find them on this page. Content content-569544 Fri, 06 Mar 2026 11:56:22 +0100 Checklist for creating your own teaching profile on JupyterHub https://www.uni-bremen.de/en/zmml/jupyter#c569544 To create a profile, you need a few prerequisites. Here is a short checklist before you start creating your profile: <ul> <li>you must be a lecturer and need a course on Stud.IP that is running in a specific semester. If you do not yet have a course, please contact the course planner in your department.</li> <li>the course should have a meaningful name (German/English)</li> <li>a short description of the course (German/English)</li> <li>which programming language(s) do you want to use (at least one is required)</li> <li>which packages do you want to install and which other extensions do you need</li> </ul> If you want to make files available via a GitLab repository, then you need <ul> <li>the link to the Gitlab repository</li> <li>and the access token to the Gitlab repository (optional, only if the repository is set to private)</li> </ul> First check whether you are registered as a lecturer in Stud.IP for the desired course. Only lecturers currently have the option of creating their own profiles and linking them to a course in Stud.IP. Teachers can authorize tutors to edit, rebuild and release created profiles. The link allows participants to be managed. If the profile is not public, only the participants of the course can see and use the profile after logging in. Another feature is that you can make teaching materials available in the profile with the help of a Git repository. Content content-593294 Fri, 06 Mar 2026 11:56:22 +0100 What options do I have with a profile – a how-to guide https://www.uni-bremen.de/en/zmml/jupyter#c593294 When creating a Jupyter teaching profile (also called a Jupyter image), you have many customization options. Below you will find a brief description of how to create a profile on the university’s JupyterHub. <h5>Creating a New Profile</h5> In the JupyterHub menu, go to “Manage Profiles” (4) and click the “Create New Profile” button (5). This opens the profile creation form. <h5>Selecting the Course</h5> The following fields will be automatically filled in: First name (6), Last name (7), and Email address (8). Select the desired semester (9). A dropdown menu will then show your Stud.IP courses for the selected semester (10). Once selected, the Course ID (11) will be filled in automatically. Add a short description of the profile, also in English (12). This can include technical or content-related notes and will appear in the profile overview on JupyterHub. <h5>Selecting Programming Language(s)</h5> Choose one or more programming languages (13a). Currently, Python, R, Java, and Haskell are available. If you need additional languages, extensions, or packages, feel free to contact us. After selecting the language, you can optionally choose matching packages – such as Conda or Mamba packages (13b), Python packages (13c), or R packages (13d). You may also manually enter packages. Additionally, you can select RStudio and Quarto as extensions (13e). <h5>Course Setup and Management</h5> A profile must initially be created by a lecturer. However, tutors often assist in teaching and may also need the ability to edit, rebuild, and publish the profile. These permissions should be set at this stage (14). Students can work collaboratively in groups (15). Group assignments are managed via Stud.IP, where students can assign themselves. <h5>NEW: Assignment Tool</h5> The new assignment tool (16) allows teachers and tutors to create, distribute, manage, and collect assignments or exercises in Jupyter notebooks. The tool provides additional features and is currently in a testing phase. If you would like to participate as a tester, we can add you to a whitelist, and the assignment tool can be selected in the form. <h5>Linking a Git Repository</h5> Optionally, you can provide teaching materials via a GitLab repository (17a). Please enter the appropriate repository link (17b). If the repository is private, you will also need to provide a token (17c). Note: The profile will be set to “read-repository”, allowing files to be read only. <h5>Public Visibility</h5> Specify whether you want to make the profile public (18). Public profiles can be viewed and used – including materials – by all logged-in users. If you opt out, only Stud.IP-registered participants, tutors, and students will have access. <h5>Saving</h5> Finally, save your entries (19). Content content-569545 Fri, 06 Mar 2026 11:56:22 +0100 Application scenarios in teaching https://www.uni-bremen.de/en/zmml/jupyter#c569545 Jupyter Notebooks can be used in teaching in various ways. You can find some initial scenarios here: <h3>Teaching programming basics</h3> Jupyter Notebooks can be used like a digital textbook to introduce initial programming concepts in various programming languages. The advantage is that directly executable examples can be integrated and exercises can be carried out in the same document. All content is made available to the learner. Teachers can vary the steps in the material, offer solutions and then provide further exercises. The advantage of the Jupyter Notebooks is that all the required documents, packages and libraries are available. Learners can therefore concentrate on the learning objective. <h3>Teaching a topic</h3> Presentation of a topic with introductory text, executable code, videos, (interactive) graphics and further references. In addition to an insight into the content, learners also have access to information on how an analysis is carried out technically and how data is processed. Subsequently, content-related tasks can be set. The advantage of the Jupyter Notebooks is that everything can be stored in a document and distributed to a course via the JupyterHub. It provides the opportunity to gain a deeper insight into data analysis, e.g. Results no longer have to be a black box. <h3>Developing a topic&nbsp;</h3> Learners develop the content of a topic within a document. They write the text, programme the code, analyse the data and present and interpret the results graphically. This very independent approach can be more or less supported by teachers, for example&nbsp; <ul> <li>by giving students preliminary work in the form of a Jupyter Notebook, which the students work on from a different angle&nbsp;</li> <li>a template that they can use for orientation</li> <li>or letting them start from scratch.&nbsp;</li> </ul> Jupyter Notebooks can be passed on and reused. This means that topics or aspects of topics can be worked on again or anew. Learners can pick up on what they have learnt and experience that scientific work always builds on each other. New and different aspects can be worked on from a notebook. Content content-569549 Wed, 14 Feb 2024 13:56:15 +0100 Notebooks, working environment and multi-user environment of Jupyter https://www.uni-bremen.de/en/zmml/jupyter#c569549 The open source software Jupyter is constantly evolving and now consists of the initial interactive documents (Jupyter Notebooks), an interactive development environment (JupyterLab) and a multi-user environment (JupyterHub). The Jupyter team takes up the new developments, implements them and expands them based on the needs of users at the University of Bremen. Content content-569552 Fri, 06 Mar 2026 11:56:22 +0100 Jupyter Notebooks https://www.uni-bremen.de/en/zmml/jupyter#c569552 Jupyter Notebooks offer the possibility to combine executable code, text and multimedia content. 40 common programming languages can be executed in the notebooks. The notebooks can be exported and passed on. The open source software Jupyter is used worldwide and the content produced can be used outside the university context. Content content-569551 Fri, 06 Mar 2026 11:56:22 +0100 JupyterLab https://www.uni-bremen.de/en/zmml/jupyter#c569551 Jupyter Notebooks are supplemented by JupyterLabs with an interactive, web-based development environment, and enable convenient working with the notebooks comparable to desktop programmes. Simple administration, editing, exporting, uploading and downloading of files is made possible by a file directory. Additional programme packages or libraries can be loaded. Debugger functions and syntax extension tools are also available. Content content-569550 Fri, 06 Mar 2026 11:56:22 +0100 JupyterHub https://www.uni-bremen.de/en/zmml/jupyter#c569550 JupyterHub is a multi-user environment. Members of the University of Bremen can log in to Jupyter using Shibboleth. The hub makes it easy to work in larger groups. Hosting on site ensures efficient and data protection-compliant working. In addition to some standard profiles for Pythen, R and Java, you can create your own profiles, which initially specify the desired programming language and can be supplemented with additional programme packages, files and learning materials that you need for your course so that students can access them easily. Content content-569556 Fri, 06 Mar 2026 11:56:22 +0100 Piloting in the SKILL-UB project https://www.uni-bremen.de/en/zmml/jupyter#c569556 JupyterHub was piloted in the <a class="externalLink" href="https://www.uni-bremen.de/skill" target="_blank" title="Opens external link in new window">SKILL-UB</a> project as part of the Geosciences Innovation Lab. SKILL-UB supports the further establishment of JupyterHub at the University of Bremen. Content content-569555 Fri, 06 Mar 2026 11:56:22 +0100 Project funding of SKILL-UB https://www.uni-bremen.de/en/zmml/jupyter#c569555 The Stiftung Innovation in der Hochschullehre is funding <abbr title="Studierendenzentriert, kollaborativ, innovativ – Lehren und Lernen an der Universität Bremen">SKILL-U</abbr> as part of the call&nbsp;<a href="https://stiftung-hochschullehre.de/ausschreibungen/foerderbekanntmachung-2020/" target="_blank" title="Öffnet externen Link in neuem Fenster">Hochschullehre durch Digitalisierung stärken</a>. Content content-569558 Fri, 06 Mar 2026 11:56:22 +0100 Contact at ZMML https://www.uni-bremen.de/en/zmml/jupyter#c569558 <a class="mail" href="mailto:info@jupyter.uni-bremen.de" title="Opens a window for sending an e-mail">info@jupyter.uni-bremen.de</a> Content