swirldev / swirl_courses

# swirl courses
This is a collection of interactive courses for use with the swirl R package. You'll find instructions for installing courses further down on this page. Some courses are still in development and we'd love to hear any suggestions you have as you work through them.
For more information regarding swirl, visit swirlstats.com or the swirl GitHub repository. If you'd like to write your own interactive content, please visit the Instructors page of our website.
Here are our current offerings, organized by level of difficulty:
#### Beginner
- **R Programming**: The basics of programming in R
- **R Programming E**: Same as the original, but modified slightly for in-class use (see below ***)
- **The R Programming Environment**
\*\*\* *R Programming E is identical to R Programming, except we've eliminated the prompts for Coursera credentials at the end of each lesson and instead give students the option to send an email to their instructor notifying them of completion. Admittedly, it's sort of a hack until we come up with a more robust solution for in-class use (i.e. an instructor "dashboard").*
#### Intermediate
- **Regression Models**: The basics of regression modeling in R
- **Getting and Cleaning Data**: dplyr, tidyr, lubridate, oh my!
#### Advanced
- **Statistical Inference**: This intermediate to advanced level course closely follows the
Statistical Inference course of the Johns Hopkins 
Data Science Specialization on Coursera. It
introduces the student to basic concepts of statistical inference
including probability, hypothesis testing, confidence intervals and
p-values. It concludes with an initiation to topics of particular
relevance to big data, issues of multiple testing and resampling.
- **Advanced R Programming**
Since our users come from a variety backgrounds, it's very hard to label material as **Beginner**, **Intermediate**, or **Advanced**. If you find something that is labelled **Beginner** to be challenging, please don't be discouraged. The first step of learning anything is to acknowledge that you are capable of understanding it. True understanding will come with time and practice.
#### Course Authors
- **Writing swirl Courses**: An interactive guides and example 
 for swirl course authors. The first group of lessons cover basics. The rest cover 
 special topics useful primarily as samples--points of departure for one's own material.
 For more comprehensive documentation about writing your own swirl courses see http://swirlstats.com/swirlify/.
## Install and run a course automatically from swirl
**This is the preferred method of installing courses.** It automates the process by allowing you to do everything right from the R console.
1) Make sure you have a recent version version of swirl:
 [code] 
2) Enter the following from the R console, **substituting the name of the course** that you wish to install:
 [code] 
For example, `install_course("R Programming")` will install the R Programming course. **Please note that course