his article was originally posted on Quantide blog – see here (Italian version).
Good news to all italian speakers who are leaning into the R world but are still a bit afraid of what they might find (or not find) on their first face to face R experience:
Who is this course for
The course is free and open to anyone who wishes to attend it.
Since the main objective is to introduce the basics of R, the course is a particularly good fit for:
- Statistics students who need a quick start to R.
- Professionals/employees who would like to start using R and need a quick roadmap of the basics.
- Anyone who would like to get into the data science field and get familiar with its tools.
When and where will the course be available
The course is already available on DataCamp’s platform. You can access it by registering on DataCamp. Click here to be redirected to the course home page.
What to expect
The course is made of six chapters. Each chapter introduces the student to a new R concept, gradually explains R core structures and tests your understanding of the concept with in-browser coding challenges.
- Introduction to the basics
- Data frames
The exercises proposed can be completed in an interactive in-browser R session and for each assignment a feedback is provided.
What will I be able to do after having attended the course
After having completed the course, you will be able to do basic data manipulation in R, use the main data structures, and do your first simple data analysis. In particular, you will have gained the basic knowledge needed to dive further into more advanced R courses.
Time needed and schedule
You can take the course whenever you like: just sign up to DataCamp and get started every time during the day when you feel like doing it. There’s no rush, you can complete the exercises at your own pace. DataCamp saves your progress and your answers so that you can look back at how you solved a particular exercise.
The estimated time needed to complete the whole course is about four hours. Once you have started a chapter you can do only some exercises, take a break and then start again from where you left. This flexible structure is perfectly suited to those who have little time here and there but at the same time would like to learn R.
It is possible to skip exercises and chapters too, but it is advisable to take the course sequentially and complete each step before going forward.
Good news: there are no requirements, you just need a PC (or a Mac 😉 ) with an internet connection. No prior knowledge in programming or data science is required.
I hope this explanation was clear, please feel free to leave a comment if you have any question.