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.
As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.
by Ziaur R•
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"
by Glauco G d A•
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.
by Marek B•
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.
by Candice J•
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.
by Sarah G•
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!
by Alberto H A•
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.
by Lee K•
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 :)
by Figo C•
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)
by Guilherme B D J•
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.
by Eugenia G•
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).
by bt19103033 R J•
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 ..... :)
by Ximena L R•
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.
by Rahul P•
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. :-)
by Colin L•
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.)
by Madhusudhan T•
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!
by Tina L L•
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.
by anjali v•
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.
by Zainul A•
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.
by Tanmay B•
It is a really nice course if you plan to complete all the 10 courses in the Data Science Specialization track. As a standalone, It is not that great a course as it basically introduces you to different things and you need to do other courses to actually learn something.
by William B B•
This is an excellent basic course. The main problem I had was understanding the computer voice at times. There is also a quiz question or two that refer to commands in Studio that are not up to date, but only a couple that I found. All in all, it's an excellent course.
by Naveen K•
Great intro to Data Science Specialization. Hoping to complete the other courses as well. Dispels my myth about Data Science is all geeky stuff. Looking forward to bust more myths.
This course is light, broad and introductory. 4 weeks is a sweet spot. Keeps you engaged.
by Apolline M•
Not much to learn, I would have liked a more thorough introduction to data science's principles.
Yet, everything is really presented step by step to make sure that all participants install correctly all tools needed for the further classes included in the specialization.
by Tony D C•
This course is perfect to get an introduction to R and RStudio and the Github. It's easy to follow and pretty fast to complete. Probably the best thing you take home from this is to have a nice setup for the following courses where you can use the tools presented here.
by MHE v A•
Very good, basic level course. Only one minor issue when working on the markup section, make sure to install TeX before you start, or R will not be able to generate a pdf. Not a major thing, but something that did frustrate me for 15 minutes while I got it all set up.
by Bernardo M F d S•
Although I understand that Data Science involves a lot of self-oriented research, more resources and recommendations for learning git basics would be appreciated. Perhaps some practical exercises before the final assignment would've ensured a better learning process.