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 15, 2020
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 Alberto H A•
May 19, 2016
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•
Jun 29, 2020
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•
Dec 04, 2017
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•
Feb 16, 2016
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•
Jan 22, 2016
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 Ximena L R•
Mar 31, 2020
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•
Jan 25, 2017
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•
Mar 31, 2020
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•
Mar 24, 2018
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•
Apr 28, 2017
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•
Apr 01, 2018
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•
Dec 21, 2017
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•
Mar 23, 2017
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•
Mar 07, 2019
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•
Nov 27, 2016
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•
Oct 23, 2016
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•
Apr 06, 2020
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 Bernardo M F d S•
Mar 09, 2018
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.
by Rok B•
Apr 04, 2019
It is a good start to data science, you don't need a background in programming. The course is aimed at 1) helping you set up R, RStudio,git and conect it to GitHub and understand it's basic functionality and 2) getting a basic understanding of what data science is.
by REDROUTHU B•
Jun 18, 2020
The track consists of 9 courses that each last about 4 weeks which are released in batches of 3 courses each month. This course introduces the very basics of R and R studio, Git and Github and a few otherthings that will be used in the data science specialization.
by Brandon T•
Nov 17, 2017
A little daunting at first but the instruction is simple and the ability to search video transcripts for tidbits basically saves me the step of taking notes. Some of the navigation was difficult in the forum, but I ended up figuring it out and posting something.
by Benjamin S•
Sep 06, 2017
Good starter content, data science background and overview of tools. Could provide more lecture time on the tools (RStudio, Git/Bash). The course is labeled for beginners, but I can see where someone without much experience could really get intimidated by
Aug 01, 2019
Well structured and nicely organized. Content is great and lays the ground rules for start of statistics using R.
Minus one start only because there's no instructor teaching the course. I would've preferred a real human voice rather than an automated voice.
by Vishnu K•
Jun 26, 2016
The videos might not seem a lot at first view, but they contain links to some of the most useful material out there. The mentors on discussion boards are immensely helpful as well. For the uninitiated in data sciences, this is a great module to begin with.
by Steve S•
May 08, 2016
Good pace for the first course. A little more guidance on Git command flow would be help. However, the available Help documentation on Github did the trick. The problem was having to work primarily in the command line which provides limited feedback.