The content is good, but there are numerous technical problems in the course. Frequently there are references to "copy the code" which is only present in a video frame, so you can't copy it. There are also references to "follow the link" and there is no link to click on. Sometimes you can type it in from the slide, but other times there are no links given. Some of the questions in the self-assessment do not have correct answers. I can verify this by taking the self-assessment multiple times and choosing a different answer each time and never getting it right. Some of the questions are also miscategorized in the wrong lessons self-assessment.

Candid but respectful comments......

Some of the lecture material seems outdated. What we are seeing is often different than what is being presented. Is your content up to date? Lectures are quite good. When we have a serious technical issue, who can we reach out to for quick assistance? In my case, for some reason when I attempted to download and open R Studio, download was fine, the file executed as expected, but the application was nowhere to be found on my computer. This is not good because I can't begin R pranking without it. I have reached out vendor and am waiting for response. Concerned. Other than that am liking what I see

The course begins with the instructors' explanation that they created the course using text-to-speech instead of recorded instruction with a real person in order to more easily keep the code and instructions updated. However, at least in my experience, some of the instructions seem to be outdated and do not work on Mac OS. This meant I had to look to other online resources to find the needed instruction, as well as go through a trial-and-error process on my own, which was time-consuming and challenging. I would recommend that the instructors' update the course text, since the content of the course is already satisfactory.

I was really exited about taking this course as a way to learn how to use R for statical analysis. I was first surprised that the course is taught by a robot and not a person. After getting over that, I realized this class is not meant for beginners. I am someone with no programming background, my husband who is an engineer has had to do the class with me for me to be able to complete the lessons. It seems like you need some programing knowledge to be able to follow the instructions. The positives are that this course teaches you how to install R and R studio. I am hoping the the following courses are easier to follow.

This course didn't teach me much about Data Science or the different areas to pursue after this introductory course. I probably could have got as much out of it as following the tutorials on GitHub and the new desktop tool. Following the tutorial which was made for windows was also a bit annoying at times. Finally I had to wait weeks to have my assignment marked and there is still conflicting information on the course page - in 'grades' it shows I didn't pass the week 4 task. On other pages it shows I did and earned 41 out of 41 points. However I can't see a confirmation of course completion.

it was little bit irritating if i may say so learning from robot. It actually made me think twice about course. Generally students find it difficult to understand or to regularly attend any online course due to a little bit of laziness or the dullness of the teaching person. Nowadays every online course and platforms are trying to make their class more easy and fun to learn. But in this course ,i know but can't understand the need of such dull method to teach in class. as i was hoping something innovative and more of a traditional way to learn from the class.

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).

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.

This course sets the stage for the rest of the Data Science specialisation.

You get a lot of textbooks for free and they cover a lot of material.

The quizzes are a little bit underwhelming, especially the first week. Too few questions, testing some questionable knowledge (eg, what other courses there are in the specialisation -- hardly a required tool in the data scientist's box).

Overall, it's a good preparation for what is to come. It managed to whet my appetite for more , however I'm not sure the course is very useful on its own.

This course talks about the basic of Data Science theory and makes you install R, RStudio and create a Github repository.

The theory part is really nice and well presented. However, the "practical" part is boring (tutorial of downloading installer and clicking in "Next", and the tests ask about RStudio interface details, such as "Which of the options below is NOT a way of creating a new project in RStudio?". And we install R and RStudio, but we don't use them. We see a bit of R Markdown, but nothing of programming.

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.

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.

Basically if you take this course you are paying money to create an account on a website and download some software (both of which you can do for free). The rest of it is a preview of the other courses in the series. The quiz questions don't correspond to the information on the slides. I successfully passed the course, but I didn't really learn anything. Now I am debating on whether or not to continue to the R programming course after reading through the reviews of that course.

The videos are not good at all it's better the latter where people discuss about the module. It's very boring to watch and listen to the robotic videos. The script bit of data for reading is quite awesome and I believe if it's possible, it's the one that needs to be edited or you can add both lecture videos and those robotics videos at the same time and learners decide which to watch. Anyway the content was relevant and challenging at some point which makes learning awesome.

Thanks

It's good only if you are already familiarized with Rstudio and GitHub. Otherwise you'll be completely lost, and better off looking for youtube tutorials.

Es un buen curso si ya estás familiarizado con Rstudio y Github, de lo contrario vas a necesitar buscar tutoriales mejor explicados e intuitivos en youtube.

En el fondo, avanzan muy rápido y se saltan muchos supuestos.

De todas formas sirve para practicar con calma, en el caso de que se tenga más intuición sobre Rstudio y GitHub.

This is a good, general introduction. A motivated student can run through it very, very quickly. As the first of ten courses, I understand that it is a very general introduction. Still, I think it could be ramped up a bit. Week 2 of the next course - R programming - is kind of a kick in the head if you're not a programmer. I feel like some of the content from R programming could have be included in the toolbox course in order to take advantage of the relatively light load.

This should be at most a 1 week course, that is free. Half the course is installing Rstudio and signing up for github. The other half of the course is simply learning what each course down the pipeline is about. Those lectures could just be tacked onto the description of each course and you would get the same thing out of it.

I think this course would be improved by more instruction on what git is and how to use it and maybe going over some fundamental statistical topics.

This specialization is highly rated, but that was the past. The course is decent but the Amazon Polly robotic voice is horrible. It needs a lot of work before being able to give the right type of learning experience as a human lecturer. Shame.

Also, specifically this course - I haven't seen a single things that is so "new" that the team could not keep up with normal videos. Could have used the old videos or update every few years instead of this ...thing. Very sad

I've learned many interesting things concerning github, but the concepts taught in videos were kind of inadequate in some cases. I had to google some things in order to understand exactly the concept. Finally, I am not pleased with the peer graded assignment because even though I had it all right (Correct), someone gave me low mark resulting in stuck in the final stage. I had to re-submit THE SAME assigment to mark me again, and finally recieve the certificate.

This is definitely not a beginner friendly course. Only definitions were covered rather than actually showing how they work. Github part was confusing. Markdown part was not explained at all. You need to be good at searching for your query on google if you want to take up this course but that's something you need to do for every course out there. No single course is complete but still, in this R course you need to be really good at doing google search.

The course was generally good and did get the basics covered. However, I feel like there was a lack of sufficient effort put into guiding students through any common problems that may occur while downloading and first trying to use R, RStudio and R Markdown. Additionally, some of the information was out of date, forcing me to go on the internet to find different ways to access or download certain things. But overall, it got me started working with R!

The course was exceptionally planned and executed. One big problem that I had with the course were the automated videos; I can't say for others, but I wasn't at all comfortable with an AI voice teaching me the course content. I don't think I can ever get used to that. I would rather take a course that's 10 years old, 80-90% valid but has a human teaching me the course content. Other than that, I enjoyed the course. Thank you!

This course accomplishes what it says it will, but boy is it boring. If you are not already experienced in data science, it also requires a fair amount of imagination to picture what all these tools are actually used for. I would have preferred to have these tutorials integrated with the more substantial courses in the specialization. That way I could see how these tools fit in to an actual project.

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.

It has a lot of potential but it would really benefit from slowing down and explaining steps a little more slowly such as integrating R Studio and Git, and how to use Git and push from R studio to Git. For an online course, there's no need to rush through this content and judging from the comments in the forums, many people have problems with their instructions, or lack of.