Perfect Course!

Very Engaging

Great class!!

Great Course

Very useful

Nice course

Very cool!

Very good.

Excelente!

Fantastic!

Muy bueno

Very Good

good one

nice

Nice

T

+: I reached my goal for the course and now I understand a bit about R. I succeeded to pass within much shorter time than anticipated course duration. The course certificate is posted to my Linkedin profile.

-: No human mentors on the course discussion forum - all questions answered by other students. Automatic tests in swirl are too restrictive and do not accept perfectly correct student solutions slightly different to those anticipated by the authors. Week 2 assignment is much different from the reading material. Nothing taught about charting in R.

Overall comment: I think it is good value for money.

All in all good stuff. A couple of comments:

Swirl grading should be a little more flexible; sure cut is more succinct that nested ifelse's, but there's more than one way to skin the data-analytic cat in R, as I'm sure y'all are aware.

Also, I recommend more emphasis on data tables. I use them exclusively due to the dramatic performance improvement over data frames. And in my brief experiments, dplyr and tidyr commands worked on them too.

This first course was review for me. Nonetheless I definitely learned a few practical things that will up my data science game (which can always use upping).

There are a few areas of the course that are not fully explained and cause extra time trying to 'figure it out'. I am not referring to code/learning, but the logistics of the class. However, there are a few questions in assignments & quizzes that refer to things that were not particularly explained either in the lecture or in the book. I understand self study is beneficial, but I start the course with the understanding that questions will be based off of lecture or the book. If additional resources are needed, then that should be expressly stated in the lecture or book.

This course has a perfect combination of theory and hands-on exercises. I've been doing a few courses in Data Science on Coursera and I have found this method the best at least for me personally. I will probably carry on doing these courses. On the negative side, the student forum is practically dead, don't count on getting any help there. Coursera support have been very difficult and I had to wait a while to get my certificate. In the meantime Coursera charged me for an extra month (after I'd completed the course).

Une initiation intéressante et complète à R qui a l'avantage de donner des bons réflexes pour coder rapidement. Le caractère interactif des exercices de programmation est un gros plus. Attention : il n'y a pas de vidéos hormis la vidéo d'introduction. On peut aussi avoir des difficultés de syntaxe susceptibles de nous bloquer un bout de temps, notamment sur des fonctions où la documentation est un peu aride (je pense à cut et à spread sur lesquelles j'ai bien passé 1/4 du temps que j'ai consacré au total à ce MOOC).

The course is good, it concisely teaches the basics of R and it is based on chapter 1 of the book Mastering Software Development in R, so there are almost no videos, just readings. I recommend it if you have little experience with R and want a quick upgrade. However, there are some errors and typos in the material, including the final quiz. Besides, forums are mostly supported by students, the answers from mentors were from some years ago, and I have seen people with difficulties to contact the support.

I found this course quite interesting because sometimes we learn about modeling techniques, but we forget one of the most important things: how to write a good script by applying useful packages or functions to read and manage datasets. It has been an easy course and I recommend it to people who want to start basic reading and managing data with R-project. In addition, the possibility of deciding your own work schedule is very helpful when you have to do other stuff from the university.

Excelent course to start with the basics of R language. It gives a modern introduction to R programming avoiding traditional topics like loops and conditionals keeping them for more advanced programming topics. It also covers almost all tidyverse packages with a shallow introduction to the most common packages.

I have acomplaint. The dataset for the final quiz was outdated, I managed to pass the quiz guessing variable names.

The course book is good and a nice resource. Swirl lessons were also really nice. They are interactive and helped becoming familiar with the functions. However, video tutorials on real datasets like the one from week 4 would be helpful. Also, the final quiz was disproportionally difficult in comparison to what was taught during the weeks leading up to week 4. Overall a good course that provides a solid introduction to R.