R with RMarkdown and Quarto training course

Introduction to R and RStudio
●    What is base R and what are (), [] and {} for in the R language?
●    Getting comfortable with using RStudio for writing and running code
●    How to use RStudio projects to improve the reproducibility and transportability of your code.

Introduction to wrangling with the tidyverse
●    How does the tidyverse benefit us?
●    Using the {readr}, {dplyr} and {tidyr} packages for data wrangling
●    Working with Excel workbooks via {readxl}
●    Cleaning data with the {janitor}, {lubridate} and {stringr} packages

Introduction to data visualisation with {ggplot2}
●    What are the purposes of aesthetics, geoms, scales and themes in the {ggplot2} grammar of graphics?
●    Using {ggplot2} for quick EDA visualisations
●    Using annotations and {ggtext} to add richness to the stories your dataviz show
●    Creating custom themes for {ggplot2} to mirror your brand identities
●    How to create pixel perfect {ggplot2} charts for inclusion in your RMarkdown and Quarto reports

What are RMarkdown and Quarto?
●    RMarkdown has been an established tool in the R community since 2016
●    RMarkdown allows you to generate HTML, PDF, MS Word, PowerPoint and even more output types
●    Quarto is the future of RMarkdown - it will allow users of Python to generate all the same output formats as R users.
●    While this course does not explicitly cover Python you will be shown how both Python language and users can be incorporated into Quarto projects.
●    Assume that everything shown in RMarkdown will have an equivalent in Quarto
Doing exploratory data analysis with RMarkdown
●    Using RMarkdown as a literate programming environment (like Jupyter notebooks)
●    Basics of Markdown syntax for building up the story of your analysis
●    Adding and running code chunks to RMarkdown for running code
Creating interactive HTML content with RMarkdown
●    Creating HTML simple HTML reports
●    Creating HTML slides with {xaringan} in RMarkdown
●    Creating HTML slides with revealjs in Quarto
●    Customising the appearance of HTML output types with CSS
●    Advice on integrating RMarkdown customer dashboards

Creating print quality reports with RMarkdown
●    Using {pagedown} to create paginated reports
●    Using CSS to control page breaking in {pagedown}
●    Using RMarkdown to generate MS Word documents
Making many reports with RMarkdown
●    Imagine you need to generate a report for several regions, e.g. England, Northern Ireland, Scotland and Wales. RMarkdown allows you to generate a parameterised template that will pull in data from multiple sources and export a report file for each region.
●    Imagine you need to generate a report on a schedule, eg every quarter. Parameterised RMarkdown reports make it easy to programmatically generate these reports automatically.
Simplify repeated BI requirements
●    If you need to make the same chart for multiple clients/markets this can be done programmatically with the {purrr} package
●    You will be shown the basics of parallelisation to significantly speed up repeated tasks written in R code.