Course prerequisites¶

Ain’t no workshop good enough¶

The reality of workshops like these is that they really don’t teach attending folks all they need to know to subsequently apply the respective content sufficiently, not to mention the training aspect. At best, workshops provide folks with the materials, overview and pointers necessary to continue and actually dive into the taught topics (the truth hurts sometimes, doesn’t it?). Another important aspect that is frequently overlooked is that attendees usually need a certain set of skills and experience to really benefit from a given workshop, especially considering the diverse backgrounds folks have. We want to be fair, open and welcoming to everyone and while we know that we unfortunately can’t achieve and assume a truly similar level of training and experience across all participants, we can at least do our best to work towards certain opportunities. That being said, workshops like the one you’re currently looking at, by default (should) require basic to advanced programming skills and knowledge about file handling/input/output, signal processing, statistics and linear algebra (vectors much?). Tough stuff, eh?

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Let there be pre-workshop training¶

So what can we actually do to provide the entire attending gang with the chance to get up to speed for the workshop and ideally beyond? Unfortunately, we can’t hold pre-workshop-workshops and various consultations. Instead we decided to utilize the fantastic jupyter-python-open science world and build upon the framework of jupyter books employed to host this workshop and its materials. In other words, we assembled a stack of short tutorials that cover most of the aspects mentioned above. As the rest of the content, they are jupyter notebooks that can be run interactively (via the little rocket on the top right) or locally (via the download button on the top right) and mix theoretical background with actual code so that folks can familiarize themselves with the corresponding topics. Important: we know that everyone has a lot of stuff to do and that not everyone will be able to go through the stuff we collected here. Y’all: don’t worry about that, it’s chilli-milli. We will try our best to bring the core points across, even if you don’t have a substantial amount of experience. Please just make sure that you ask all the questions that might pop up, the same holds true for any problems you might encounter. Long story short, here are the topics organized from basic to advanced skills and concepts.

Introduction to the (unix) command line: bash

Introduction to git and github

Introduction to the jupyter ecosystem & notebooks

Introduction to Python

Introduction to NumPy

Introduction to SciPy

Introduction to Visualization in python

Introduction to Statistics in python

Introduction to scikit-learn & scikit-image

Using Python for neuroimaging data - NiBabel

Using Python for neuroimaging data - Nilearn