HELLO WORLD! <3

| What | A place to ask questions about code/data (and hack). | | Who | Anyone with data/desire to learn. | | When | 4-5 PM on Wednesdays: 9/4, 9/18, 10/2, 10/16, 10/30, 11/13, 12/4, 12/11 | | Where | The Green House, 505 E Washington St, Iowa City, IA 52240 | | Why | So many reasons. |

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What is Hacky Hour

Hacky Hour means different things at different Universities/Institutes. At the University of Iowa, Hacky Hour is an informal gathering of people to share knowledge and ask questions about their data and how to code analyses for their data.

Who attends Hacky Hour

Whether you're creating software, teaching coding, or collecting your first dataset, you are welcome at Hacky Hour. This is place to learn and share, so people of all experience levels are encouraged to come!

Here is a non-exhaustive list of the types of people that come to Hacky Hour.

• Undergraduates
• Graduate Students
• Postdoctoral Students
• Professors
• Librarians
• Research Staff

Why attend Hacky Hour

There are a lot of reasons to attend Hacky Hour, see if any of the listed scenarios resonate with you.

• You saw a cool method in a paper and they even shared their code, but you do not know how to install/use the tool because it is not well documented.
• You've inherited code from another graduate student who has since graduated and the code has mysteriously stopped working.
• You are interested in learning how to code.
• You want to automate some data entry, data analysis, or visualizations.
• You have some code written and want to know how to version control the code so you can keep track of all the changes being made.
• You want to make the code more reproducible/sharable.
• You want to see how other people are using code to help with their research.
• You have an interest/desire to help others improve their own coding ability.
• You want to find opportunities for collaboration.
• You want a dedicated time/space to solve that data analysis problem.
• You want to commensurate with others that are also trying to learn how to code on their own.
• You wrote some code, but you are unsure how to test if it is "correct".

This list is also non-exhaustive, so if you have some data/code/questions, stop by and see if Hacky Hour helps.

Code of Conduct

We at Hacky Hour are dedicated towards providing an inclusive environment for everyone to learn and feel welcomed. If we are not holding up to that standard, please contact [email protected]. We follow the code of conduct put forth by Brainhack. Hacky Hour adheres to the constitution of Iowa City BrainHack. A copy is available on the University of Iowa's Engage site.

Other Tech Groups/Resources

• Statistics Outreach Center (SOC)
• Women in Computing Sciences (WICS)
• Students in Technology and Science (SiTS)
• HackIowa
• Iowa Social Science Research Center
• Datascience Institute
• techcorridorio
• UI3
• Neuroimaging Workgroup
• Library Data Services
• Statistics Colloquia
• High Performance Computing
• CLAS Linux Group
• Institute for Clinical and Translational Science: Informatics Core

HackHour Inspiration

• HackyHourHandbook

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Free, open-source texts

• MATLAB
  • Programming with MATLAB (Software Carpentry): http://swcarpentry.github.io/matlab-novice-inflammation/
• Python
  • Programming with Python (Software Carpentry): https://swcarpentry.github.io/python-novice-inflammation/index.html
• R
  • Programming with R (Software Carpentry): https://swcarpentry.github.io/r-novice-inflammation/index.html
• Version Control
  • Version Control with Git (Software Carpentry): https://swcarpentry.github.io/git-novice/index.html
• General
  • MIT online course "The Missing Semester of Your CS Education": https://missing.csail.mit.edu/
  • Introduction to Programming in the Biological Sciences Bootcamp: https://justinbois.github.io/bootcamp/2022/
• Neuroimaging
  • Neurohackademy Courses: https://neurohackademy.org/neurohack_year/2022/
  • Neuromatch Academy Courses: https://academy.neuromatch.io/courses

Tutorial notebooks/files

• MATLAB
  • MATLAB fundamentals and EEG Analysis (Jax Skye, Marco Pipoly, Gail Harmata, Ethan Rooke, Trevor Cline, Kerry Tarrant): https://brainhack-uiowa.github.io/uibrainhack2021/
  • Matlab Workshop Fall 2021 (Dr. Victoria A. Müller Ewald): https://uihackyhour.github.io/matlabfall2021/
• Python
  • Python fundamentals and some neuroimaging: https://brainhack-uiowa.github.io/uibrainhack/
  • Transcription of Al Sweigart's Automate the Boring Stuff With Python (Trevor L. Cline and Kerry Tarrant): https://github.com/UIHackyHour/AutomateTheBoringSweigart

Resources recommended by ITS Research Services

• Python resources:
  • Learn Python - Full Course for Beginners: https://www.youtube.com/watch?v=rfscVS0vtbw
  • The official Python tutorial: https://docs.python.org/3/tutorial/
  • Python tutorials: https://www.learnpython.org/en/Welcome
  • Pandas tutorials: https://pandas.pydata.org/docs/getting_started/index.html#getting-started
  • Python Data Science Handbook: https://jakevdp.github.io/PythonDataScienceHandbook/
• R resources:
  • Book: “Cookbook for R”: good to start with: http://www.cookbook-r.com/
  • Learn R at the Console (interactively): the swirl package: once you have installed R and can install packages, the "swirl" package is an interactive way to learn R: https://swirlstats.com/
  • Book: “R for Data Science”: learn to use R for data science: https://r4ds.had.co.nz/
  • Article: “The Layered Grammar of Graphics: good to learn more about graphing in R": http://vita.had.co.nz/papers/layered-grammar.pdf
  • plotly examples: https://plotly.com/r/
• Jupyter resources
  • Try Jupyter for free in your browser without installing anything. Click on “Jupyter Notebook” under the “Applications” section to try Jupyter Notebook and see tutorials for Jupyter Notebook: https://jupyter.org/try
• Other data analytics resources, free for UI members:
  • LinkedIn Learning: on-demand online training library: https://its.uiowa.edu/linkedin-learning
  • The Iowa Social Science Research Center’s workshops: https://ppc.uiowa.edu/research-support/workshops

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