I've spent my PhD learning what turns out to be work-from-home friendly science. I also incessantly keep notes & links.

So, here are lists of all the resources I know for learning data analysis, open-source development, open-access data and open-science practices, etc:
Quick note / disclaimer: this is somewhat tuned to cognitive neuroscience / electrophysiology - but a lot of it is also pretty general.

Also, the overview and links for everything included below is also here: https://github.com/openlists/Overview
For programming, Python is a powerful open-source and general-purpose language with a vibrant user community.

Here is a list of resources to learn both standard library and scientific Python: https://github.com/openlists/PythonResources
Version control is a useful and important aspect of working with code.

This is often done using git (the tool) and Github (a place to store and share projects managed with git).

Here is a list of resources to learn git & Github: https://github.com/openlists/GitResources
Working with data requires specific skills relating to the data-types. For analyzing time series in neuroscience, this includes a lot of digital signal processing.

Here is a list of resources to learn about digital signal processing (DSP): https://github.com/openlists/DSPResources
Open-access data is great for exploring and testing hypotheses, and learning and developing new analyses.

Here is a list of open-access electrophysiology data (EEG / MEG / ECoG / LFP): https://github.com/openlists/ElectrophysiologyData
With some data, and some computing and analysis skills, one still needs dedicated tooling for managing and doing data analyses.

Here is a list of open-source software tools related to electrophysiological data analysis (EEG / MEG / ECoG / LFP): https://github.com/openlists/ElectrophysiologySoftware
Lots of questions can be answered with available data, though at some point one still likely wants to design new experiments, which typically include tasks.

Here is a list of open platforms, tools and available implementations for behavioural tasks: https://github.com/openlists/OpenTasks
As one does research, it is useful to keep in mind what concepts and ideas one is using, and how this relates to everyone else in the field. What are the core concepts and words people use?

Here is a list of ontologies related to neuroscience: https://github.com/openlists/NeuroOntologies
I'm not the only one who keeps lists of things - there are also a lot of other useful lists out there!

So, here is a list of other lists that also list out resources and materials (related to computing, neuroscience, science in general, etc): https://github.com/openlists/OtherLists
So that's basically everything I know about!

Lists are open to contributions / suggestions / additions, etc.

I hope this can be useful for sharing resources, especially in the field of cog-neuro / electrophysiology. I'm also open to ideas to develop / organize / share, etc.
I forgot to mention up top, but if it's not clear the basic concept of "openlists" (the collection of all these lists that I'm linking to) is to list out useful and *open* materials. Everything listed should be completely open and free to access / use, etc.
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