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  • diff --git a/_site.yml b/_site.yml index 3defc27..7963654 100644 --- a/_site.yml +++ b/_site.yml @@ -10,9 +10,9 @@ navbar: - text: Set-up icon: fa-clone href: set-up.html - - text: Data + - text: More Tutorials icon: fa-clipboard-list - href: data.html + href: nextsteps.html - text: Daily Notes href: notes.html - text: Contact diff --git a/aboutyou.html b/aboutyou.html index 48439db..52bda8c 100644 --- a/aboutyou.html +++ b/aboutyou.html @@ -198,10 +198,10 @@
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  • diff --git a/nextsteps.Rmd b/nextsteps.Rmd new file mode 100644 index 0000000..118babc --- /dev/null +++ b/nextsteps.Rmd @@ -0,0 +1,35 @@ +--- +title: "Continuing your learning" +output: + html_document: + include: + before_body: header.html +--- + +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. + + diff --git a/nextsteps.html b/nextsteps.html new file mode 100644 index 0000000..18955cb --- /dev/null +++ b/nextsteps.html @@ -0,0 +1,309 @@ + + + + + + + + + + + + + +Continuing your learning + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    Here are resources for continuing your learning of the topics that you studied this week:

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    Intro to R

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    More R Workflow

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    Forecasting and Exponential Smoothing Models

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    Rob J Hyndman (lead on the forecast package) and George Athanasopoulos have an excellent online text on practical forecasting and exponential smoothing.

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    Shiny Apps

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    Start with RStudio’s online tutorial for shiny apps.

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