My favorite course, at least it gives me an argument why scripted statistics is awesome and can be applied to a number of data related activities. Recycling chunks of code has proven useful to me.
A very important course that greatly improved my ability to communicate the findings of any sort of data analysis that I perform. This is a critical skill to acquire to "deliver the means."
автор: Anton K•
The material is shallow. Projects are way too time demanding. Everybody knows that data cleaning is a routine and long process. That is precisely why nobody likes it. And if there's only one way to clean the data - by hand and only after reading a lot of related database documentation - this kills all the fun of studying and makes the overall picture of consepts relations unclear.
автор: Jaymes P•
This course was not well organized. It seemed like lessons were just thrown together and covered much the same content. Some were recorded lectures, others filmed in an office, saying virtually the same things with nearly the same slides but on different weeks. Same old story with the instructor--impossible to listen to because of all the so, um, uhhh, so, kinda, so ummm, etc.
автор: Gonzalo A D•
The course is poorly organised: There is a project on week one that requires knowledges of week two. Some concepts are dictated more than once because it uses videos made for this course + other recorded from a class room.
I think this course should be a 3 weeks project and the price should be the half of it cost.
Though I enjoyed the second project.
автор: Gianluca M•
It is not a bad course, but it is very little informative. There is some nice general discussions about data science by the teacher, there is the explanation of the package knitr, and little else.
As part of the data science specialization it is nice. As a stand-alone course, I would definitely not recommend it.
автор: Julien N•
Very disappointed by this course (was used to better by JHU)!
Nothing more than a R Markedown tutorial
Not up-to-date (a full video about an deprecated R package).
A section about evidence based analysis that is hard to understand (and of questionnable interest if not to "fill" this rather empty course)
автор: Roberto M•
This course seems 'light' in content - too much time is spent reviewing case studies instead of discussing different ways to create documents that enable reproducible research. Perhaps this should be a topic/chapter in another course, and not a standalone course.
автор: Marvin T O•
Reproducible research with doubt is important but videos and what it is discuss are not appealing and beyond that, what are worthen are the projects. I did not learn so much from the videos but by myself. Though, the forum is very useful.
автор: Matt E•
This section could have been completed in a two week schedule instead of four. It is not a terribly complex subject. Statistical inference, however, is. It has a lot of content and could easily go for 5 or 6.
автор: Jackson L•
This leaves a lot to be desired. I felt the lectures were fragmentary at best and really lacked in depth analysis. A lot of time was spent on the philosophy of analysis rather than practical tools in R.
автор: Willie C•
Lecture videos were very repetitive. Course projects were repetitive, too. Important information, but didn't need to be stretched out over a full "four-week" course.
автор: Abhimanyu B•
Provides a very summary overview of a very important aspect of data analysis. Expected more!
автор: Johnny C•
The course was interesting, but it is bad many of the videos are recorded lectures.
автор: Pratik P•
Sholdnt be a different course. It shold be very very concise. Not this long.
автор: Victor M•
Last two weeks do not teach anything new
автор: Cyriana R•
ok, but the focus is too much on knitr,
автор: Sindre F•
Useful for academics.
автор: Avolyn F•
I was really passionate about the subject matter, but, although I have experience in R, apparently not enough to complete the assignment. Would have liked a little more warning that this would be needed, I was more interested in the topic of Reproducible Research, which while I agree is easier done via code of some kind, shouldn't be a topic specific to R, should be applicable to Python, SQL, whatever.
Might have time to revisit this, but will probably need to take a few more R classes to even be able to complete, likely won't get around to it, but the first 2 weeks were worth the cost of paying for a certificate, I guess.
автор: Joel K•
The other modules that I have done in this specialisation have been great. The lecturers are insightful and the courses have been at the right pace. This particular module was flat, to say the least. I paid €43 to learn a small amount of markdown syntax, and the quizzes and the weeks didn't even match up!
автор: matthieu c•
The course presented an important topic, but it was not new to me. Moreover I believe that the quality of some audio track is not good enough to understand everything the lecturer is explaining. I'm referring to Roger Peng lecture with the students.
автор: Stefan H•
Very repetitive in context of earlier introduction to the topic and also throughout the weeks. Generally it doesn't feel there is much of a take-away and not sure it deserves its own course.
автор: YAN N W T•
Not much to take in this course comparing to the previous courses. Worst of all video lectures are not well organised.
автор: Anand M•
Too much repetition; one video has been stretched into 10.