adding prep page

Author: noahbenson

prep.md

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+
+# Preparing for NeuroHackademy
+
+This page contains information for preparing for NeuroHackademy! Not everything
+suggested on this page is required; we expect you to chart your own path
+through the program, with this page serving as a convenient reference.
+
+Setup and Technical Information NeuroHackademy uses a
+[JupyterHub](https://jupyter.org/hub) cloud-computing server for lecture
+materials and hack projects. The JupyterHub provides an interface to Jupyter
+notebooks and terminals running on virtual machines remotely in the cloud. We
+have provisioned these virtual machines to have all of the software tools and
+configuration details that we typically need for projects in the course, and
+the machines should have plenty of computing power and memory for our purposes.
+
+Critically, because we use remote virtual machines, you do not need to do
+anything to setup your laptop for the course aside from having a contemporary
+web-browser installed. If you would like to install tools like Python, the
+terminal/shell, and git on your local laptop, [this page, maintained by the
+Carpentries organization, has instructions for installing these tools
+locally](https://carpentries.github.io/workshop-template/install_instructions/).
+
+To connect to the JupyterHub, direct your browser to
+[https://neurohackademy.2i2c.cloud/](https://neurohackademy.2i2c.cloud/). Authentication
+is performed using your GitHub credentials, so after clicking the “Log In to
+Continue” button followed by the “Log On” button, you should be prompted for
+your GitHub username and password.
+
+## Logistics
+
+Logistical information about travel, housing, and internet can be found on
+[the Logistics Page]({{site.baseutl}}/logistics)!
+
+## Review Resources
+
+You do not need to review any particular material prior to the
+NeuroHackademy—for topics like Python programming we will have lectures
+in two tracks: introductory Python and advanced topics. However, if you are
+interested in brushing up on some of the topics we cover, here are some useful
+resources.
+
+### Software Carpentry
+
+The Carpentries is a not-for-profit organization that publishes and administers
+public lessons on basic data science tools. [The Software Carpentry lessons
+website](https://software-carpentry.org/lessons) contains a listing of their
+basic lessons on the UNIX shell (also frequently called BASH or the terminal),
+Python, Git/GitHub, and R. These lessons are written with commentary so that
+individuals can walk through them on their own, but it is also fairly easy to
+find in-person recordings of these lessons as lectures via YouTube (just search
+for “Software Carpentry”).
+
+### Python Data Science Handbook
+
+This book, by Jake VanderPlas, is a somewhat more advanced reference for data
+science topics in Python. It is highly recommended for intermediate and
+advanced scientist programmers, and it is open source. [This page has basic
+information about the book](
+https://github.com/jakevdp/PythonDataScienceHandbook), including a link to a
+free version online.
+
+### Previous NeuroHackademy Lectures
+
+Most of the lectures from previous years of the NeuroHackademy were recorded
+and can be viewed on YouTube. These lectures are organized by year and schedule
+on the [neurohackademy.org website's lecture archive](
+{{site.baseurl}}/archive). Here are several of the past lectures organized by
+topic rather than year; note that this list is mainly focused on basic data
+science skills, so past lectures on specific neuroscience topics may not be
+shown.
+
+#### Git and GitHub
+* [Version Control with Git and GitHub (Elizabeth DuPre, 2020)](https://www.youtube.com/watch?v=ErzGfcBoLg4)
+* [Using Git and GitHub for Collaboration, Part 1 (Ariel Rokem, 2021)](https://www.youtube.com/watch?v=Lsmt2rHPJDU)
+* [Using Git and GitHub for Collaboration, Part 2 (Ariel Rokem, 2021)](https://www.youtube.com/watch?v=j3IbFKksJkQ)
+
+#### Introductory Python
+* [Introduction to Programming in Python (Tal Yarkoni, 2020)](https://www.youtube.com/watch?v=5KgyMerXYz8)
+* [Introduction to Programming in Python, Part 1 (Noah Benson, 2021)](https://www.youtube.com/watch?v=Swb-UptFRl4)
+* [Introduction to Programming in Python, Part 2 (Noah Benson, 2021)](https://www.youtube.com/watch?v=ycGWr5Zy2A0)
+* [Data Manipulation in Python (numpy/pandas) (Tal Yarkoni, 2020)](https://www.youtube.com/watch?v=EwCGCJk7YH0)
+* [Creating Sharable Python Libraries (Ariel Rokem, 2020)](https://www.youtube.com/watch?v=ACycTncrJWA)
+
+#### Advanced Python
+* [Numerical Computing in Python (J.B. Poline, 2019)](https://www.youtube.com/watch?v=ZmNpURWhcZM)
+* [Data Visualization (Kirstie Whitaker, 2020)](https://www.youtube.com/watch?v=uaKu5a6P3oU)
+* [High Performance Computing (Ariel Rokem, 2020)](https://www.youtube.com/watch?v=4pCeUMOVfIs)
+* [Parallelization with Python/dask (Ariel Rokem, 2022)](https://www.youtube.com/watch?v=7k4d_7F7dz4)
+
+#### Machine Learning and AI
+* [Introduction to Machine Learning (Tal Yarkoni, 2020)](https://www.youtube.com/watch?v=zvd8M8dwHxM)
+* [Machine Learning with Scikit-Learn (Tal Yarkoni, 2019)](https://www.youtube.com/watch?v=epjZDEPRFsI)
+* [Deep Learning (Ariel Rokem, 2019)](https://www.youtube.com/watch?v=nzJ7A1KevSk)
+* [Introduction to PyTorch (Noah Benson, 2021)](https://www.youtube.com/watch?v=OCpmJ9LPMlc)
+* [Deep Learning and CNNs (Noah Benson, 2022)](https://www.youtube.com/watch?v=RT7gI-VN4dE)
+
+#### Docker
+* [Docker (Chris Gorgolewsky, 2020)](https://www.youtube.com/watch?v=4s0vNSt-3j0)
+* [Docker, Part 1 (Noah Benson, 2021)](https://www.youtube.com/watch?v=tewf5ZRZHkE)
+* [Docker, Part 2 (Noah Benson, 2021)](https://www.youtube.com/watch?v=4zQfSBYdKFY)
+
+#### Cloud Computing
+* [Cloud Computing for Neuroimaging (Tara Madhyastha, Amanda Tan, and Ariel Rokem, 2020)](https://www.youtube.com/watch?v=X5XvkdE6vgU)
+* [Cloud Computing (Naomi Alterman, 2022)](https://www.youtube.com/watch?v=qbRkD9tDHQE)
+
+#### Neuroscience Tools and Data
+* [Workflows/Nipype (Satra Ghosh, 2020)](https://www.youtube.com/watch?v=YjJ9-gxlRJk)
+* [NiBabel: Neuroimaging data and file structures in Python (Chris Markiewicz, 2020)](https://www.youtube.com/watch?v=Y6ulmOlW1FI)
+* [Nilearn (Elizabeth DuPre, 2020)](https://www.youtube.com/watch?v=ASEyg5nxj3A)
+* [Nipreps (Oscar Esteban, 2020)](https://www.youtube.com/watch?v=J_ZwPN8gYpM)
+* [Brain Imaging Data Structure (BIDS) (Kirstie Whitaker, 2020)](https://www.youtube.com/watch?v=XzfjxbTYQRM)
+* [Working with multimodal data in the Brain Imaging Data Structure (BIDS) (Dora Hermes, 2024)](https://www.youtube.com/watch?v=kCqCfqweAAs)
+* [Introduction to the Geometry and Structure of the Human Brain (Noah Benson, 2020)](https://www.youtube.com/watch?v=LRZwZAvdJgw)
+* [Machine Learning for Neuroimaging (Elizabeth DuPre, 2023)](https://www.youtube.com/watch?v=shAmKXAfjW4)
+