minor corrections

workshops/programming_r.qmd

@@ -14,9 +14,9 @@ categories: [R, tidyverse, purrr, functions, iteration, programming]
 
 # Description
 
-This is a one-day, hands-on workshop intermediate R users who use the tidyverse and want to improve reduce the amount of duplication in their code. You will learn the two main ways to reduce duplication: creating functions and using iteration.
+This is a one-day, hands-on workshop intermediate R users who use the tidyverse and want to improve and reduce the amount of duplication in their code. You will learn the two main ways to reduce duplication: creating functions and using iteration.
 
-We will use a tidyverse approach to cover function design and iteration. When writing a function you will learn how to deal with "data masking", give default values to arguments, give unspecified arguments and what side effects are and how to manage them. In the afternoon, you will learn how to iterate across the columns of a dataframe using `across()`, what "anonymous" functions are and how to read and write multiple files using **`purrr`**.
+We will use a tidyverse approach to cover function design and iteration. When writing a function you will learn how to deal with "data masking", give default values to arguments, give unspecified arguments, and what side effects are and how to manage them. In the afternoon, you will learn how to iterate across the columns of a dataframe using `across()`, what "anonymous" functions are and how to read and write multiple files using **`purrr`**.
 
 # Audience
 
@@ -30,8 +30,8 @@ This course is for you if you:
 
 # Instructor(s)
 
-|                               |     |                                             |
-|------------------|------------------|------------------------------------|
+|                      |     |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
+|-------------------|-------------------|-----------------------------------|
 | ![](emma-rand.jpg)   |     | **Emma Rand** is a Senior Lecturer in the Department of Biology at the University of York where she specializes in teaching data science and reproducibility, particularly to those who do not see themselves as programmers. She leads a UKRI funded project called Cloud-SPAN which trains researchers in cloud-based high performance computing for 'omics. She is a Software Sustainability Institute Fellow, a Teaching team lead for R Forwards and delivers data science training for the Royal Society of Biology and the Biochemical Society. |
 | ![](ian-lyttle.jpeg) |     | **Ian Lyttle** is a Data Scientist at Schneider Electric. His technical interests include visualization, interactivity, and functional programming. He is a community contributor to tidyverse and r-lib, and maintains CRAN packages including vegawidget and boxr. He has delivered tutorials on a variety of R topics at UseR!, Uncoast Unconf, and the Iowa State University Graphics Group.                                                                                                                                                       |