> For the complete documentation index, see [llms.txt](https://docs.aisl.science/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aisl.science/external-tools-and-services/notebook-services.md). # Notebook Services Browser-based notebook platforms can be useful for teaching, exercises, data analysis, and machine-learning experiments without requiring students to configure a local environment. {% hint style="warning" %} These are **external services** and are not operated by AISL or FHNW. Free plans, compute quotas, hardware availability, privacy practices, and terms can change. Check the provider's current conditions before relying on a service for a course or project. {% endhint %} ## Noto (EPFL) [Noto](https://noto.epfl.ch/) is EPFL's centralized JupyterLab platform for education. It runs entirely in the browser and supports Python, R, C, JavaScript, and Octave. **Free resources:** Standard Noto provides free computing for teaching and learning. EPFL currently documents a maximum allocation of **4 GB RAM and 2 CPUs per user**. GPU-enabled GNoto resources are separate and provided on request for suitable courses. **Access:** FHNW users can sign in with a **SWITCH edu-ID linked to their FHNW organizational identity**. Noto is open to users from Swiss universities in the SWITCH network. **Best for:** Course exercises, demonstrations, assignments, and lightweight Jupyter-based teaching with almost no setup. * [Open Noto](https://noto.epfl.ch/) * [EPFL Noto information](https://www.epfl.ch/education/educational-initiatives/cede/teaching-interactively/jupyter-notebooks-for-education/one-click-access-to-jupyter-notebooks-online-with-noto/) ## RenkuLab [RenkuLab](https://renkulab.io/) is a collaborative data-science platform developed by the Swiss Data Science Center. It connects code, data, compute, and browser-based development environments such as Jupyter and VS Code. **Free resources:** Creating projects and running sessions in the **public compute tier is free**. The available resource classes can change with the platform configuration. Public sessions currently auto-pause after about **2 hours of inactivity** and are shut down after **2 weeks** if not resumed. **Access:** Accounts can be created using **SWITCH edu-ID**, GitHub, or ORCID. **Best for:** Reproducible projects that combine notebooks, repositories, datasets, collaboration, and configurable compute. * [Open RenkuLab](https://renkulab.io/) * [Renku documentation](https://docs.renkulab.io/) ## Kaggle Notebooks [Kaggle](https://www.kaggle.com/) provides hosted notebooks with free CPU and accelerator resources alongside datasets, models, competitions, and learning resources. **Free resources:** Kaggle currently documents notebook sessions of up to **12 hours for CPU/GPU** and **9 hours for TPU**, with **20 GB of autosaved working storage**. CPU sessions provide **4 CPU cores and 30 GB RAM**. Free GPU access includes NVIDIA P100-class resources; the weekly GPU quota is typically **30 hours and can sometimes be higher depending on demand**. TPU access is documented at up to **20 hours per week**. **Access requirements:** A Kaggle account is required. **Phone verification is required for accelerator access**; Kaggle may apply additional verification requirements to some newer features or accounts. Hardware and quotas are subject to availability. **MCP:** Kaggle also provides an official remote **Model Context Protocol (MCP) Server** for accessing Kaggle resources from compatible AI clients and agents. **Best for:** Data-science exercises, public datasets, machine-learning experiments, competitions, and free GPU/TPU notebook workloads. * [Open Kaggle](https://www.kaggle.com/) * [Kaggle Notebook documentation](https://www.kaggle.com/docs/notebooks) * [Kaggle MCP Server](https://www.kaggle.com/docs/mcp) ## Deepnote [Deepnote](https://deepnote.com/) is a collaborative cloud notebook designed for data science, teaching, and team-based analysis. **Free Education plan:** Students, teachers, and researchers can qualify using an institutional email address. Each member of an Education workspace currently receives **unlimited Basic-machine hours with up to 5 GB RAM and 2 vCPU**. Advanced machines and GPUs require a payment method, and the free Education plan does not include advanced compute, Scheduling, or Deepnote AI. **Access:** Sign up and verify your **FHNW school email address** to request the Education plan. **Best for:** Collaborative notebook teaching, group assignments, shared classroom workspaces, comments, and real-time editing. * [Open Deepnote](https://deepnote.com/) * [Deepnote Education](https://deepnote.com/docs/edu-overview) * [Education plan verification](https://deepnote.com/docs/edu-verification) ## Google Colab [Google Colab](https://colab.research.google.com/) is Google's hosted Jupyter Notebook service with free CPU access and optional GPU and TPU runtimes. **Free resources:** Colab provides free access to GPUs and TPUs, but **does not publish fixed accelerator quotas or guarantee specific hardware**. Limits, idle timeouts, GPU/TPU types, and availability change dynamically. Free notebooks can currently run for **up to 12 hours**, depending on availability and usage patterns. **Access:** A Google account is required. Free accelerator access is subject to Colab's dynamic usage and anti-abuse limits. **Best for:** Quick notebook experiments, teaching examples, Google Drive integration, and occasional GPU/TPU workloads where fixed capacity is not required. * [Open Google Colab](https://colab.research.google.com/) * [Colab FAQ and resource limits](https://research.google.com/colaboratory/faq.html) ## Choosing a service | Service | Good starting point for | Free compute highlights | | ---------------- | ----------------------------------------------- | ----------------------------------------------- | | **Noto** | FHNW/Swiss university teaching | 4 GB RAM, 2 CPUs per user; SWITCH edu-ID | | **RenkuLab** | Reproducible research and project collaboration | Free public compute tier | | **Kaggle** | ML exercises and accelerator workloads | CPU plus weekly GPU/TPU quotas | | **Deepnote** | Collaborative classroom notebooks | Unlimited Basic-machine hours on Education plan | | **Google Colab** | Quick experiments and examples | Dynamic free CPU/GPU/TPU access | --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.aisl.science/external-tools-and-services/notebook-services.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.