Lectures were a little disappointing but I learned a lot with the programming assignments. The assignments were difficult and quite time consuming but worth the effort.

The course is not for absolute starters, i recommend having some background of R prior to taking this up. The assignments and exercises are good to gain some knowledge

Hay mucha diferencia entre la teoria y ejemplos presentados y las actividades que debemos realizar en R por nuestra cuenta. Falta explicación de estos ejercicios.

I could not complete it as 100% because of a bug, in week 3 quiz and week 1 quiz. in week 1 2questions will never get a correct answer. Same case with week3 quiz.

Video lectures were not very engaging. Assignment No. 2 causes student frustration unnecessarily. There's other and better ways to encourage a hacker mentality.

The lectures were good but the assignments were just too hard for me, I was really lost... I think there is a great difference between lectures and assignments

Don't get me wrong, I did learn R programming from this course. But it was not well designed and the assignments didn't always mesh with what was being taught.

For whatever reason, my biggest complaint is that the coursework did prepare me very well for the assignments. This was frustrating and somewhat inefficient.

The programming assignments are way over the level for this course. Is nice to make it hard but too many things I never fully understood from the assignments.

Very very tough for the beginners. Without high background knowledge of statistics, only having the programming skills are not enough to complete the course.

The course had too much stuff crunched (and poorly explained) in too short a time period. That said, I got something out of it using a self-directed approach.

There's a gap between what's covered in the lesson and the assignments. I had to go elsewhere to fill in those gaps. Otherwise, this is a very useful course.

Assignments were way harder than what was taught in the videos, did not pay attention on various objects used in R and also on how to correctly write codes.

The course is too old to be relevant for current environment. There were certain functions that were used in the early weeks, but explained in later weeks.

Huge gap between difficulty in assignments and lectures leads to frustration at times., but overall the course is good. The swirl exercises are excellent.

For an introductory level class, the progression of the classes could have been more gradual. Classes and assignments seemed a bit disconnected at times.

There is a large gap between the course material and the assignments. Requires A LOT of extra research to complete if you do not have prior R experience.

Nice course, but the gap between video lessons and programming assignments was too wide for me. Would have loved more guidance towards the assignments.

Course content was good, but assignments were way too hard and not related to course content. I have to spend long hours online to do the assignments.

more programming assignments and long course duration to introduce a step-by-step learning about the features of R can be done to facilitate learning.

Overall good, but some major information missing for completing assignments, + very hard to understand the speech of the lecturer Peng in some cases.

I think this course could have been twice as long with all the material that was covered in it, especially compared to the Data Scientist's Toolbox.

To less MP to understand what's the core processing method in R, but over all a nice language course for someone who has learned CS courses before.

R Programming is seeming difficult more hour courses are required to be initiated for making this language better learn among scientific community.

It seemed like course material had little to do with the assignments. Teach us how to read alphabets and assignment is to write poetry. Big jump!