Workshop Series

We are hosting a virtual workshop series during fall semester 2023 to help UA researchers improve their reproducibility and data science skills

Objectives

• Become comfortable with sharing and collaborating on research products on GitHub using git
• Learn approaches for how to better organize research projects and their corresponding code, including intermediate R skills
• Be able to document projects in several ways, including Rmarkdowns and READMEs

This workshop series will not cover statistical methods or modeling, mathematics, introductory R, or any other programming languages besides shell, git, and R. These topics can be taught separately by request.

Prerequisites

You should take this workshop if:

• You are a graduate student who has collected their data and is ready to analyze and document it, or a researcher or postdoc who is looking to further skills in the areas outlined above
• You are working on research projects that could benefit from improved collaboration, documentation, and organization
• You are comfortable with introductory R skills
• You do not have any prior experience with version control, or want a stronger foundation

Structure

The complete lesson materials will be taught over ten sessions (see topic and dates below) consisting of code-along learning, through which participants will iteratively build and practice their skills. Then, participants will apply their new skills to personal research projects. We will host two follow-up sessions to: 1) check-in for updates and problem solving, and 2) showcase student projects. 

This workshop series been previously offered at University of Arizona. 

Apply

If you are interested, complete this application form! It should take no more than five minutes and requires no prior preparation. We will start notifying applicants on August 14, 2023, and then have rolling admissions until the application closes on August 28, 2023. The workshop will be limited to 20 total participants, with priority given to researchers in ALVSCE (including CALS departments) and those who can commit to at least 10 of the 12 sessions. 

If you have any questions, please reach out to the instructors Eric Scott and Kristina Riemer!

• Read more about Fall 2023 Workshop Series: Reproducibility and Data Science in R

There are over 100 packages that extend the functionality of ggplot2 to allow you to make just about any data visualization you can think of! In this workshop we’ll cover a few of our favorite extensions and show you how to find the ggplot2 extension that meets your data visualization needs.

• Read more about Part 3: Exploring the wide world of 'ggplot2' extensions

If you know how to make basic plots with `ggplot2`, but struggle to add on finishing touches like specifying colors, customizing axes, adding text to plots, and creating multi-panel figures, then this workshop is for you!

• Read more about Part 2: Crafting publication quality data visualizations with 'ggplot2'

In the first of a 3-part series, you'll gain a better understanding of the "grammar of graphics"—the theory underlying the `ggplot2` package. Using practical examples, you'll learn how understanding the grammar of graphics can help you build more creative, complex, information-rich visualizations.

• Read more about Part 1: Understanding the foundations of 'ggplot2'

The CCT Data Science team is offering a workshop series during spring semester 2022 to help UA researchers improve their reproducibility and data science skills. This opportunity is available to all researchers in ALVSCE.

Objectives

• Become comfortable with sharing and collaborating on research products on GitHub using git
• Learn how approaches for how to better organize research projects and their corresponding code, including intermediate R skills
• Be able to document projects in several ways, including Rmarkdowns and READMEs

This workshop series will not cover statistical methods or modeling, mathematics, introductory R, or any other programming languages besides R. These topics can be taught separately by request.

You should take this workshop if:

• You are a graduate student who has collected their data and is ready to analyze and document it, or a researcher or postdoc who is looking to further skills in the areas outlined above
• You are working on research projects that could benefit from improved collaboration, documentation, and organization
• You are comfortable with intro R skills
• You do not have any prior experience with version control, or want a stronger foundation

Topics for each session are listed below, and you can look at more detailed lesson materials. This workshop series has been taught previously and successfully to a group of ESA SEEDS researchers.

Eight workshop sessions will meet twice weekly through the month of February and will be hands-ons walkthroughs of content. After, participants will be able to apply new skills to their research projects. We will have a followup session for updates and problem solving, and then a final session the first week of April for short, no-slide demonstrations of progress.

If you are interested, please fill out this application form! It should take no more than five minutes and requires no prior preparation. We will start notifying applicants on December 15, 2021, and then rolling admissions until the application closes on January 17, 2022. In order to provide one-on-one help and create a collegial atmosphere, we will be limiting the total number of participants to 15 for this workshop series.

If you have any questions, please reach out to the instructors Jessica Guo and Kristina Riemer!

• Read more about Spring 2022 Workshop Series: Reproducibility and Data Science Skills

We are hosting a virtual workshop series during fall semester 2022 to help UA researchers improve their reproducibility and data science skills

Objectives

• Become comfortable with sharing and collaborating on research products on GitHub using git
• Learn approaches for how to better organize research projects and their corresponding code, including intermediate R skills
• Be able to document projects in several ways, including Rmarkdowns and READMEs

This workshop series will not cover statistical methods or modeling, mathematics, introductory R, or any other programming languages besides shell, git, and R. These topics can be taught separately by request.

Prerequisites

You should take this workshop if:

• You are a graduate student who has collected their data and is ready to analyze and document it, or a researcher or postdoc who is looking to further skills in the areas outlined above
• You are working on research projects that could benefit from improved collaboration, documentation, and organization
• You are comfortable with introductory R skills
• You do not have any prior experience with version control, or want a stronger foundation

Structure

The complete lesson materials will be taught over ten sessions (see topic and dates below) consisting of code-along learning, through which participants will iteratively build and practice their skills. Then, participants will apply their new skills to personal research projects. We will host two follow-up sessions to: 1) check-in for updates and problem solving, and 2) showcase student projects. 

This workshop series been previously offered at University of Arizona. 

Apply

If you are interested, complete this application form! It should take no more than five minutes and requires no prior preparation. We will start notifying applicants on August 12, 2022, and then have rolling admissions until the application closes on August 26, 2022. The workshop will be limited to 20 total participants, with priority given to researchers in ALVSCE (including CALS departments) and those who can commit to at least 10 of the 12 sessions. 

If you have any questions, please reach out to the instructors Jessica Guo and Kristina Riemer!

• Read more about Fall 2022 Workshop Series: Reproducibility and Data Science in R