Friday, February 9, 10am-12pm
R Programming: R Basics
Register: https://go.wisc.edu/5728tw

Learning how to code can be intimidating, but will save you time and effort in the long run. This workshop will cover the basics of R programming. By the end of this session, you will be able to create variables, use pre-defined functions, understand data types, and load and inspect a dataset using RStudio.

This workshop is geared toward programming novices, so no previous experience is required.

Friday, February 16, 10am-12pm
R Programming: R Basics (repeat)
Register: https://go.wisc.edu/4irmwh

This workshop is an exact repeat of the February 9th “R Programming: R Basics” workshop (see above).

Friday, February 23, 10am-12pm
R Programming: Data Wrangling
Register: https://go.wisc.edu/43l6v6

Data is rarely perfect out of the box. This workshop will cover how to manipulate datasets using an R package called dplyr. After this session, you will be able to select rows and columns, add new columns, remove missing data and create summary tables of your data.

A basic working knowledge of R and RStudio (functions, operators, data types) would be helpful for you to get the most out of this session.

Friday, March 1, 10am-12pm
R Programming: Data Visualization
Register: https://go.wisc.edu/71r9a3

So you’re familiar with R, but want to do more with your plots than the base graphics package. This workshop will show you how to use the ggplot2 package in R. After this session, you will be able to create a variety of plot types, alter their aesthetics, and create custom themes.

A working knowledge of R, RStudio, and dplyr would be helpful for you to get the most out of this session.

Friday, March 8, 10am-12pm
R Programming: Reports
Register: https://go.wisc.edu/p3d136

One way to automate your reports is to create files with human readable text and machine readable code. This workshop will cover creating reproducible reports of this type using RStudio. After this session, you will be able to create R markdown documents, add formatted text and executable code blocks, and render the document into a final report.

A working knowledge of R and RStudio would be helpful for you to get the most out of this session.

Friday, March 15, 10am-12pm
R Programming: README Files in RStudio
Register: https://go.wisc.edu/gp5ml2

Documenting your analysis in a way that is understandable to a colleague (or yourself 3 months later) can be challenging. README files are text documents that record your computational environment, methodologies, and more. After this session, you will be able to create a README file template in RStudio.

A working knowledge of R and RStudio, and some experience with R markdown would be helpful for you to get the most out of this session.

Tuesday, February 6, 10am-12pm
Python Programming: Introduction
Register: https://go.wisc.edu/p69s6d

This workshop is for the absolute beginner wanting to slowly walk through the process of getting started with Python, a programming language commonly used for data analysis. We’ll work through installation and setup of some helpful software and introduce basic concepts and terminology used in Python. Finally, we’ll work together to create your first simple but useful program!

This workshop is geared toward programming novices, so no previous experience is required.

Tuesday, February 13, 10am-12pm
Python Programming: Introduction (repeat)
Register: https://go.wisc.edu/0yr37t

This workshop is an exact repeat of the September 19th “Python: Introduction” workshop (see above).

Tuesday, February 20, 10am-12pm
Python Programming: Loops, Lists, and Functions
Register: https://go.wisc.edu/28tooa

This workshop will take a deeper dive into Python, covering essential topics such as automating tasks using loops, lists, and functions.

Prerequisite: Understanding of basic Python concepts (i.e. variables, data types) is helpful.

Tuesday, February 27, 10am-12pm
Python Programming: Spreadsheets and Data Manipulation
Register: https://go.wisc.edu/6xbv4i

Real-world data can be messy. This workshop will cover a range of topics related to organizing and manipulating spreadsheet data for more effective analysis. We’ll use pandas, a popular and free data analysis library written for Python.

Prerequisite: Understanding of basic Python concepts (i.e. functions, operators, data types) is helpful.

Tuesday, March 5, 10am-12pm
Python Programming: Data Visualization with Seaborn
Register: https://go.wisc.edu/6sok43

In this workshop, we will explore different methods and tools for visualizing data. We’ll use seaborn, a popular and free data visualization library written for Python.

Prerequisite: Understanding of basic Python concepts (i.e. functions, operators, data types) is helpful.

Tuesday, March 12, 10am-12pm
Python Programming: Batch Processing and Working with Image Collections
Register: https://go.wisc.edu/34619b

This workshop will focus on using Python to make bulk changes to files and file directories. It will also introduce Pillow, a free and beginner-friendly Python library for processing image files.

Prerequisite: Understanding of basic Python concepts (i.e. functions, operators, data types) is helpful.