nextsteps.Rmd

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title: "Continuing your learning"
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Here are resources for continuing your learning of the topics that you studied this week:

## Intro to R

* [Software Carpentry free tutorial](http://swcarpentry.github.io/r-novice-inflammation)

* [Data Camp free tutorial](https://www.datacamp.com/courses/free-introduction-to-r).  Takes about 4 hours.   

* You can also learn R straight from within R using the [swirl package](https://swirlstats.com/).  This doesn't require internet access except to install the package.

* Basic R introduction from [ComputerWorld](https://www.computerworld.com/article/2497143/business-intelligence/business-intelligence-beginner-s-guide-to-r-introduction.html).

## More R Workflow

* Software Carpenter has a course that covers some of more advanced topics I did not cover on R workflow: data wrangling with dplyr, tidyverse, and more on RStudio projects.  [Reproducible Research with R](http://swcarpentry.github.io/r-novice-gapminder/)

* Eric Anderson produced a couple online courses on R workflow while with NOAA Fisheries.  [R Reproducible Research 2015](http://eriqande.github.io/rep-res-web/)  and [Reproducible Research 2017](https://eriqande.github.io/rep-res-eeb-2017/)

## Forecasting and Exponential Smoothing Models

Rob J Hyndman (lead on the forecast package)  and George Athanasopoulos have an excellent [online text on practical forecasting and exponential smoothing](https://otexts.org/fpp2/).

## Shiny Apps

Start with RStudio's [online tutorial](https://shiny.rstudio.com/tutorial/written-tutorial/lesson1/) for shiny apps.