What?

R and RStudio (1/2)

Roughly speaking (very personal opinion):

  • R is usually better for statistics;
  • Python is preferred by computer scientists and people working on very Deep Learning;
  • both are amazing for data science, graphs and simple machine learning.

R and RStudio (2/2)

Beyond statistical analyses and data science, you can do lots of things with R: reports, websites, books, applications, and slides (like these ones).
+ doc & ppt (see https://ardata-fr.github.io/officeverse/), but the latter are usually ugly.

R & RStudio can easily be combined to other languages (Python, C/C++, SQL, JavaScript, etc.).

Moreover, the R community is very inclusive and kind.

In short, R is pretty cool. 😎

The learning curve

“Failure the greatest teacher is.” Yoda in The Last Jedi.

The end of the learning curve

The philosophy of the course

Knowledge is not free: you have to pay attention.

  • Learning comes from YOU! More than 80% of what you will get from the course will come from your efforts. Passive listening \(\neq\) learning.
  • Remote teaching is a major barrier! Because attention spans are short, especially in front of pedagogical videos!
  • Remote teaching is not a major hurdle! Because anyway, progress will only be made by practice (on your computer, outside the video sessions).
  • I will always be there to help. Google & stackoverflow are your best friends. I’m next on the list.
  • To optimize my feedback, be as precise as possible. (best solution: send me files & code, not screenshots!)

Errors, errors, errors

=> Debugging!