It looked easy, but it isn't easy for anyone who is new to R programming or programming in general. If one is taking this course as part of an MSDS Degree, please familiarize yourself with some R programming before working on projects.

The class fails to teach most of what it asks for the assignments. In the requirements, only a basic understanding of R was noted, while in reality most of the assignments require you to have an, at least, intermediate understanding of R and how different R libraries work. What's worst is that none is this is really taught, but really it just feels as a very shallow, incomplete, guidethrough of 10% of the whole process. Would not recommend this course for someone who is not following the MSDS degree. You will not learn anything other than opening an R markdown.

Parts of this course were useful to get an idea of what to expect from a career in data science- particularly the interviews with data science professionals.

However, for whatever reason it's difficult to actually get assignments graded (and therefore complete the course) and the final assignment involves uploading a video of yourself speaking - I have no interest in having a video of myself floating around this website.

In my opinion the course is a little bit desorganize. The first modules consist of only videos about Data Science and then the 3rd starts with downloading Rstudio and making a data analysis in R. I thought that was a big jump and I felt a bit lost at first. Also, on peer-to-peer review, I reviewed a work from 2 years ago, that was a bit scary haha but overall it's great introdutory course on Data Science.

While the content of this course is interesting, it feels a bit disorganized. It starts strong with real world examples and professionals from companies as well-known as Google. But, it then divulges into using R to read in data, clean it and create R markdown documents for analysis. This was a fun project, but the instructor does not really teach anything here. They just use an example that is not related to the data in the project, and then they just copy and paste some R commands into the console. I had to use YouTube tutorials for pretty much all of it because there just isn't any actual teaching going on.

A great introduction to Data Science, with plenty of practical assignments that are flexible enough to explore our own questions of interest.

Exercises and lectures were hands-on and informative. I enjoyed the practical advice on data science as a profession.

Very practical overview of the field. Does require knowledge of R to do 2 simple projects if you take it for credit.

Good course, with broad overview and several specific discussions from people working in the field. My only issue is that week 3 seems to assume prior experience with R; just a little bit more support ("go here to install R", "here's a quick tutorial on tidyverse") would make it much easier to reach the level necessary for understanding the lectures and project.

In the end I have to say I learned a lot, but the lectures weren't nearly comprehensive enough and the instructions for the assignments were far too vague. I essentially had to teach myself most of what I needed for the assignments and I was left feeling like I was missing the bar, but then found that the grading criteria was more lenient than expected. It was also unclear at times what kind of document I needed to upload for the assignments. I think this content could be improved quite a bit.

This course is not worth any effort or expenditure of time. It doesn't offer any usable introduction to data science 'as a field'. Then the instructor plunges into random chunks of R code. And then there is the final assignment in the form of a video recording of an 'elevator pitch' of the results of an analysis. This is a joke.

Thanks a bunch, to Dr Jane Wall! I sincerely appreciate it. I am now equipped with valuable tools that will help me in my Data science career path. I really-really enjoyed this course. The in-depth analysis that we will be doing in Data Science will impact the world, hence, it is important to internalize all the concepts in this course. By applying the learnings from this course to the covid-19 and NYPD shootings case studies, I understood the value of preparing a good report that will help the key Organizations.

A detailed, step-by-step explanation of what is useful in data science practice.

Good course for exercise R programming, data analysis and communication skills.

It is very good course. Thank you very much professor.

got good knowledge of R

Weldon good very good

Good

Elementary.