If you are taking the Dartbrains course at Dartmouth, we provide a jupyterhub server that has all of the data, software, and notebook preinstalled. However, I frequently get emails about how to access everything if you are not a Dartmouth student.
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You can always download each notebook locally to your computer with the download button.
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For some of the tutorials that don’t involve working with the bigger imaging datasets such as the signal processing tutorial, you can run the code interactively on google colaboratory.
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In general, I recommend installing python locally your computer and all of the relevant packages. We have written a tutorial for how to do this. Then, I recommend downloading the data using datalad using this tutorial. Datalad is nice because it makes it easy to only grab the data you need when you want it. You can easily delete data when you’re done to free up space. Then you can download each notebook using 1) above, or you can directly download all of them from the dartbrains github repository. You will typically need to figure out the paths to your data and notebooks and will likely need to update the paths for each notebook for the code to work.
Please feel free to post questions in this thread or as a github issue about the installation process or suggestions on how to improve this experience.