Sep 08, 2017
It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.
Apr 24, 2018
This course was a good intro especially in setting all the necessary software for future courses. I suggest to read the manuals, books and other readings the profs suggest. The resources are helpful.
by Ahmad A•
Oct 07, 2018
the voice is too low and the level of instructing are not for beginners, but with a lot of effort you could pass
by Rajeev R J•
Sep 15, 2018
Didn't get an awful lot from this course. The videos have a lot of information which are not directly related to the course.
by Sadanand U•
Aug 19, 2018
Very basic, may be a bit more use cases on Git would have been useful. But that's just me
by Nicolas B P•
Oct 04, 2018
Not sure if we will come back to Git, but i thought that in this section it was covered way too superficially. Maybe the idea was that we should get to it ourselves, but i guess my expectation was different. Other than that, the course was ok.
by Jake P•
Apr 20, 2019
The lectures are sometimes needlessly long with a lot of superfluous talking. The course would be better with more concrete examples and THE OUTPUT OF EACH INCLUDED. The course explains very simple queries and then asks you to do complex ones in the quizzes when the examples were poorly explained. Khan academy is a much superior course to this one, yet it does not offer a course certification. If this course actually wants to teach people efficiently it should emulate the real-time learning and coding in browser that Khan Academy has.
by Nikolay B•
May 06, 2019
Hi guys. I'm not sure that you are reading the feedback, but instead of saying that it's good or bad I'm going to come up with suggestion. I'm data pipeline architect with 20+ years of experience who decided to take these courses to understand a gap of knowledge that current data scientists have. I think it comes from the very course. The R is kind of out dated for current world of big data, but I think you've already heard about this. Some Data Scientists who show up in our company they are good with theory but very bad in implementation. They don't understand the Big Data, especially distributed data. R is good language to the lessons but it doesn't have any connection with real world. You better include some basic knowledge about Spark (especially Spark ML), distributed computation and finish with R. Most of data science algorithms and libraries implemented (and used by real world) are in Python. Contact with some Cloud Providers like AWS and Google to create accounts for education. You course would be more attractive and, what is most important, would be more useful for people and companies where they start to work.
If you want, you can contact with me about some volontier consultancy. My email is firstname.lastname@example.org
by Anton K•
Jun 16, 2019
I don't agree with the order at which this course is introduced to learners. Why do we need to learn CLI and Git at the very beginning? Besides, everything in this course was sort of detached and sketchy. For instance, the intro to the types of analysis (e.g. descriptive, exploratory, inferential, and so on) is not covered well. In my opinion it would be much better to have an intro about the underlying theories and concepts in much more detail rather than learn Git command or learn how to melt and cast data (from Hadley's presentation).
by Sanket B•
Jun 15, 2019
The initial lectures were good . The Git & Github part got me little confusing , a little detailed explanation with live examples would have really helped. The last conceptual part was interesting. Some reading material just to drill down on certain Data science jar-guns would really help though it is understood that best place to find answer to question is google / forums / stack overflow...Still some reading material would really be very helpful to maintain the interest in the course.
by Woszczyk H•
Jun 20, 2019
If you already know your way around git and basic programming this is not a very interesting course.
I feel it should be included in the specialization.
by Mikołaj G•
Jul 02, 2019
Good course, but in 4 weeks you will get only basics of basics.
Jul 03, 2019
I think maybe because I have computer science background, so I think this course is too easy.
by Jacob P•
Jul 01, 2019
Seems to be somewhat useless in terms of actual content
by Tanvi M•
May 25, 2019
This course lacks the inter-activeness that holds up a class. Even the material was not worth the money as it just teaches you to install certain programs and exactly what one can do with it. I feel there is enormous scope to improve this course in particular.
Things I will suggest:
1. The installation process is not shown with a depth. I feel increasing video size wont matter as reducing and removing certain important points that students should learn. I hope a better depiction and graphical representation of such an amazing subject can be done.
2. The problem with coding is that though they told how to make certain thing bold or Italics not actually it was shown as to where to put this.
I hope that everyone gain interest in such a subject.
by Debanjan D•
May 25, 2019
Okayish course. This course will give you an introduction in RStudio and Data Science.
by Bhupendra S P•
May 20, 2019
Good for beginners.
by Ilkka N•
Jun 02, 2019
The course dealt with basic software issues on getting you ready for Data Science, and discussed briefly more conceptual topics. The contents of this course by no means would take 4 weeks to complete from anyone, so I think the time span to take this course is exaggarated. Still, it is very important course to get you started, if you are complete stranger to R, RStudio, GitHub and R Markdown.
by Aritra D•
Jul 24, 2019
A little more depth on R and R studio and the rest and more data driven projects would have been appreciated
by Xin T•
Jul 23, 2019
by Oren T•
Aug 10, 2019
Human Interaction is missing.
by Chengming X•
Aug 14, 2019
I have to say the text to voice translation of the text to video lacks good rythm, sometimes it is not easy to follow all the detial espatially there never is natural pause after some touch ideas or steps to me. As a class of introdution level to layman like me I think it could be better introducing more practical examples to practice, or I would like to see some links to external study materilal, that would make the class experience even better to avoiding frequently searching for troubleshooting.
by Suhas K•
Apr 24, 2019
I wish there were more exercises for the project.
by natanael m d l•
Sep 16, 2019
This course is very introductory and very short, so that most of the things presented in the course were familiar to me.
by Jairaj A P•
Aug 26, 2019
i felt this course was very disorganized. It introduces terms and concepts not explained before. There was an assignment on creating forks. This process was not in any lecture. Of course, with R and GitHub you can find anything on internet.
The lectures narrated by Amazon Polly is very boring. It also messes up some of the terms.
by Чмуров М В•
Sep 21, 2019
не представляет ценности в качестве отдельного от специализации курса. весь курс является просто введением по специализации
by Jani R•
Sep 02, 2019
This course was far too easy.