This page covers frequently asked questions (FAQs) about the R and Python workshops provided by Information Technology Services - Research Services (ITS-RS) at the University of Iowa.

Table of Contents:

What tools do I need to participate in the workshops?

Depending on the workshop, JupyterLab or RStudio will be available in the Interactive Data Analytics Service (IDAS). Workshop materials will be available in IDAS. After registering for the workshop, participants will be given access to the workshop instance in IDAS, which lasts for the duration of the workshop.

A link to log in to IDAS will be shared at the beginning of the workshop. Participants do not have to request an IDAS account. Participants will need to log in with their HawkID and authenticate with Two-Step Login (Duo).

The workshops are entirely virtual via Zoom. Cameras and microphones are optional. Participants may use the Q&A feature in Zoom to ask questions.

We will use several features in Zoom, including Q&A, reactions, chat, and live transcription. Please update your Zoom desktop client before the workshop, and log into Zoom using your University of Iowa account, so that you can take advantage of all Zoom features.

Is there any cost to attend the workshops?

No, there is no cost to attend the workshops. However, workshops are only available to current University of Iowa faculty, staff, and students, who are employed by the University or enrolled in a class at the University at the time of the workshops.

Each workshop may have prerequisites; please see the workshop description on the UI calendar for more information.

I’m not able to attend the workshops but I still want to learn. What should I do?

The good news is that Python and R are open-source programming languages, which means there are a lot of free resources to study on your own if you have time! Here are a few free resources:

1. 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/
Scikit-learn user guide: https://scikit-learn.org/stable/user_guide.html
"Probabilistic Machine Learning: An Introduction" and "Probabilistic Machine Learning: Advanced Topics" by Kevin Murphy: free pdf drafts of books: https://probml.github.io/pml-book/

2. 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
RStudio Education resources for beginner, intermediate and expert levels: https://education.rstudio.com/learn/
plotly examples: https://plotly.com/r/

3. 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

4. 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

Will the workshops be recorded?

The workshops will not be recorded. Future workshops will be posted on the UI calendar as they are scheduled, typically at the beginning of each Fall and Spring semester. You are welcome to subscribe to our email list to receive an email when we announce our workshop schedule. Please see above for a list of free resources to learn Python and R.

I can’t attend all sessions of the workshop. Can I attend only one of the sessions?

Each workshop is split into multiple days to reduce Zoom fatigue and encourage reviewing of the materials between sessions. Since later sessions build on previous one(s), participants might have difficulty following along if previous materials are missed. Participants are encouraged to attend all sessions to learn the complete contents of the workshop. However, it is up to the participants to decide how many and which days of the workshop they want to attend. Each day’s agenda is posted in the workshop description to help participants understand what topics will be covered; please see the workshop description on the UI calendar for more information.

Will you offer workshop X again? / I’m interested in topic X. Do you offer workshop in that topic?

Thank you for your interest in our workshops. ITS – Research Services offers workshops in R, Python, High Performance Computing (Argon), and Linux. We typically offer the following workshops every year:

R workshops: (recommended to be taken in this order)
- Introduction to Data Analysis Using R
- Interactive Data Visualization Using Plotly in R
Python workshops: (recommended to be taken in this order)
- Python for Data Analysis: Python Fundamentals
- Python for Data Analysis: Introduction to Pandas (being evaluated for combining with the Python Fundamentals workshop)
- Python for Data Analysis: Machine Learning with Python
Introduction to Linux Using Argon (Schedule TBD)
Introduction to High Performance Computing Using Argon (Schedule TBD)

Workshops will be posted on the UI calendar as they are scheduled, typically at the beginning of each Fall and Spring semester. You are welcome to subscribe to our email list to receive an email when we announce our workshop schedule. We will continue to improve our workshop offerings to meet the needs of the research community as we are able.

Whom do I contact if I have more questions?

Please contact the ITS - Research Services team at research-computing@uiowa.edu if you have any questions.

Python and R Workshops FAQs