It was a little to easy and the quizzes were not really necessary. Questions like "What courses are in the Data-Science Specialization?" don't help to controll my learning progress. However for a first, introducing course it was okay. R Programming is way more interesting and challenging <3

Didnt enjoy the voice on the automated videos, but was faster at reading than watching videos. The document didnt work for the Big data Section and had to watch the video for this. Good introduction and wished I had more questions to practice! Looking forward to R Programming section next"

It's a good start point for people who wants to start pursuing a data science career and haven't a statistical background. Explain the basic definitions of research analysis types and shows the very beginning of handful tools like how a git repository works and good editors for R scripts.

The course was good except for the updates that it needs. To link Github and RStudio, you need to create a personal access token on Github and use that as the password when it is prompted on RStudio. There is no mention of personal access tokens in the course so that needs to be updated.

The course is very basic but still contains useful information both on data science and some of the tools.

Unfortunately, because of how basic it is, I found the quizes focusing on trivial and subjective questions that are both hard to answer and not really testing any interesting skills.

i think is good course they explain to you Data science and all things about it and how to install and use the tools of data i think the problem is the robot that they used as speaker i think the voice of human better than robot for me and the translation for Arabic isnt really good .

One would need to do some additional hard research in between though to complete the course due to the automated video which skips a couple of steps including the discussion on the Git! Hope this will not be the case on the rest of the courses. overall Good course but 5 stars for me.

The tools needed are all explained well, including installation. Still getting used to the new Amazon Polly format. A few questions in quizzes seem to not align with updated material, but that could just be an intentional push to be resourceful. Looking forward to the next course.

Overall a really nice course for looking into Data Science. I would've liked more on the general field of what is data science and what kinds of problems you might solve, etc. But the lectures were good and the timing was very manageable for working professionals to do. Thank you!

This course was amazing, mostly teaches how to manage your work as a Data Scientist. Essentially it's is a great course to take if you feel like you have no idea on how data science workspace is managed. I found GitHub to be a very useful tool! I will defs be using it in the future.

I found this course to have very useful material and good, clear explanations. My only criticism is that the last of the four weeks has practically no content. There are no lectures and the only assignment is grading the assignments of other students, which at most takes 20 minutes.

The part on how GitHub works (Including the Git Bash) section could be further discussed for a better understanding of how to use the platform. Overall it's a good course! well structure. just that content could be more detailed so that it will be a even more meaningful course :)

Great learning on the basics of Data Science and it's importance in real-world applications. Help to get started with introduction to Python, R Language, Git!

Lectures could perhaps be more engaging and have more visual appeals (instead of having just lots of words on most slides)

This a beautifully desined course to introduce someone completely beginner in the field of Data Science. But i gave 4 star because there should be more description of the things like R Markdown, git, github etc. Also there should be more tools included not enough tools included.

This course is good to get all your programs set up before you start your studies in Data Science.

I think it could offer a little bit deeper knowledge of git and github in order to guarantee it will not be a problem later, since they will not be strictly related to data science.

The course content is very useful, but explanations are short and It's unclear how to install R studio for the Windows (I found it at Youtube). Also I had a problem how to install the R packages, and solution was simple: you should run it as administrator (it wasn't in lecture).

This course is the beginner course , in which you will learn about the basics and get to know the tools you need to develop your career in DATA SCIENCE field. This was the optimal course to get you familiar with what basically is data science. You only need a question ..... :)

I felt like I was able to keep up with the course material fairly well. My only critique would be when it comes to using git, the commands aren't very intuitive to me. Maybe explaining the commands a bit more would be more helpful, i.e. what the commands are telling git to do.

Very nice introduction! Unlike a lot of online courses, this course is no fluff or jargon. It is solid stuff with hands on experience. I only wished this course was longer. After completing the 10-week Machine Learning course by Andrew Ng, this course felt a bit too short. :-)

The course is interesting ... however, the teaching is very minimalistic in terms of visualizations and explanations. I would prefer a real teacher - however with the electronic voice and some more and better designed ppt slides you could achieve better results ! Stay on ;-)

Very basic. A few tweaks are needed in the last quiz's questions - the one pertaining creation of a .md vs. a .rmd file, and how to make sure the "## " prefix is properly given. (There should be a space after, and graders need to look at the raw file, not the presented view.)

An interesting introduction to data science, Git and GitHub. Hope GitHub is explained in a little more detail. Quite a few people found a couple of problems with the final project. The community is great and there are people who will help. Looking forward to the next course!

The course is great but there are some serious glitches happening in the Coursera platform that desperately need attention. I just went from showing that I did not pass the peer review section and in the next second was greeted by a big green Course Completion Certificate.

This course is a great introduction to what data science essentially is and all the necessary tools required to start your analysis. However, it would be great if the examples used in the videos were explained a bit more in context rather than being stated plainly.

Thanks!

A little unclear about the process for using Git & Github. The common functions/code are thought, but I believe a demo or a video review for the last assignment should be shared. Other things in the course provide a good introductory insights to the world of Data Science.