The video is simple and good.

But the final project and some test are too hard based on material presented.

Also staff's support are not good.

The only interesting part was dplyr. The rest was too confusing, with lots of lists and no explanations.

The information in the lectures is very stale, which makes it extremely frustrating to learn from.

The course material needs update. There are code snippets that do not work.

This course could have been better. It was all textual and it got boring.

Final assignment is not well detailed, and may cause confusion.

This course lacks projects to implement the skills we learn.

The course was a bit mixed in terms of its quality.

Very poor instructions for assignments.

waste of time for software engineers

Too many things in one place

Worst class in this series.

too superficial

Boring.

2

R is really just the worst, and the instructors do not make it better. The code in this class is unreadable:

- too many one liners, because "it's faster to write", though harder for other people to read

- variables are named cryptic things like spIns or x, rather than names with meaning (eg, sprays.by.insect), again "because it's faster to type"

- way too many cases of "there is more than one way to do it", which just makes things confusing because the other ways tend not to be equivalent

What I'm most concerned about is that I've seen lots of poorly written code in many different languages: Java, C++, C, Python, Perl, and now R. But I've also seen really well-written code in all the languages *but* R, I have yet to see any code in R that is flexible, maintainable, and clear. Which leads me to think that no such code exists, or it's so rare that it doesn't matter. It is clear to me that if I am to do data analysis, then I will need a different set of tools; but because this specialization is taught entirely around R (the lectures are about R, not about higher-level concepts), then this specialization is not useful to me.

This course is about getting data from the web and processing it using a computer language and packages in that language that are under active development. There is a github repo with course content and other electronic resources that are made to be easy to update. It has never been updated, even once since the course first went live 4 years ago. There are many broken links, several new features and bugs in packages that make lecture content obsolete or broken, errors found by students, etc. None of these issues have been addressed, even once, in any of the material, including the extremely easy to update content on github. This is disappointing and not very professional. Additionally, many of the notes are not particularly good to begin with. Much of it is essentially cribbed from other online tutorials, examples in the documentation, and in a few cases, someone else's (also broken) lectures. Take this course if you want a study group (the forums are actually quite useful) to help you go through 4 year old lectures rehashing online tutorials from 4 years ago about a topic that changes pretty quickly.

There is a lot of fluff in this course and at the same time it assumes that you have knowledge and skills that are not covered in this course or in the previous two (e.g. github). I'm really disappointed in the quality of this course--specifically at how vague many of the instructions were in the quiz questions and the final project-- and that most the time when explanations were asked for on the message board the professors just did some hand waving and said that figuring it out was part of the assignment. That isn't teaching (online or otherwise). And if your instructions aren't clear, you aren't doing the job of an instructor when you pass the buck and try to sell it as "part of the learning experience." I hope this fall off in quality isn't reflective of the rest of the courses in the data spec.

Made it all the way to week four and decided to drop this entire specialization. The data set in the final project is poorly referenced (despite the code book provided). The data set comes in 24 text files you have to merge (which isn't a problem in R) but what is a problem is when you don't understand what the variables and observations are. Perhaps if I worked in the medical field these measurements would mean more, but to a business major, they are incomprehensible with the limited documentation provided. So my assumption was, if I am having difficulty understanding what the final data structure should look like, others will be having the same problem......and its peer reviewed. How can I possible grade someone else

For such a terrible course to then change payment terms without my authorisation. Take $64 from my account without telling me clearly amongst all the other junk mail. Coursera have a lot to answer for, and this specialisation is not even worth wasting your time if it was free.

Taught without purpose; meaningless instructions given to copy without regard of the bigger picture.

First quiz states 10 minutes for a 5 question quiz. I am taking way longer due to errors in loading packages and Java. One of the question is out of date and has not been updated in a year. Quality of this course is lacking when changes are constant. The mentors say it's realistic. I'd considering dropping this course and search for a better updated one.

This was a mix of everything course, nothing was completely explained. It would have been a better idea to just pick a limited options and cover them well. The description of the final project was a puzzle and the objective behind it was completely vague. I wanted to quit in the middle, but I put time and that is why I finished it!!!

Lectures and other material just don't cover the information needed in the course project. Majority of the learning has to be done outside of this course, in order to pass the course project.

I cannot recommend this course anyone who is not deeply familiar with the topic already. The course project is truly frustrating!

Expected more explanation with the teaching part, detailed lecture depicting live examples is needed to explain each and every module of the course. similar examples like Assignments can be taught by hard-coding them with RStudio

hoping that these things can change with the next courses which I'm enrolling

MUito rápido o conteúdo e o fato do suporte ser somente o fórum deixa o curso vago, achei muito fraco os slides e o método de ensino.

Poderiam focar mais em exercícios e nos comandos mais difíceis, pois quando chega nos assignments fiquei perdido por não ter conseguido realizar da forma esperada.