Learner Reviews & Feedback for Developing Data Products by Johns Hopkins University

good course

Indispensable for anyone who wants to make a career in data science. I recommend.

very good

This course provided a great number of methods used to deliver a data project.

This is the ninth course of a series of nine courses. The creation of the apps and the didactics is very good, I just needed to do the first course of the series to get to work better the fundamentals, since this course is a bit advanced.

I loved the experience and everything I learned, I would say it is well worth it!

Best class of the specialization. The assignments were actually instructive.

This is an excellent course. It's not as hard as the last three in the sequence but there is plenty to experiment with, and I was very pleased to see that we learned how to build packages, methods, and classes along the way, created an app, and even delved into building our own Swirl tutorials. While not strictly part of creating a data product, those are great things to have on the resume. I was pleased to see the capabilities of Plotly and will certainly use that. As with all of these courses, you must pay close attention to the marking rubric to get full marks. Onward to the Capstone!

Excellent course!

Extraordinario Curso

It is a good course provide neccessary stuffs for data science.

You can skip week 4 as it is done previously in other courses . Small and good course.

Excelent introduction to the topic and really fun to use!

excellent Course

This class includes a lot of introductory content an a good measure of hands-on practice. It also provides a great amount of resources and reference material for the learners to expand their knowledge further.

Interesting course but some topics don't have motivation

It is a nice class but many of the topic were already covered on previous class of the specialization. If this is the only class you will take, it is okay but it you are taking the whole specialization this is like doing few (not all) things again

Really good course, but for the time invested I think they could have gone a bit deeper in some areas. I enjoyed it though :)

good content

Great course. but I think some lesson should be together in one week and add presentation lesson more.

I have learned a lot. The course is simple and very useful. Maybe the assignments should improve because the directions are a bit vague, but in general I liked it.

should have been more indepth

great course

Taken this course in its old fashion style. Now reviewing the new design was a little bit displacing, but I ascribe this to the fact I've done all the specialization courses in the old design.

However the structure of the course is quite good. Some typos were reported, as well as a bug on the unanswered questions in quiz 3. Main worst point was the missing format of several text boxes. I would have appreciated paragraphs, bold and italic, some links, picture, not only raw plain text.

Overall review is nonetheless over the average.

Awesome course. Overview of all the things you need to become part of the data science community in terms of contributing and sharing.

In general, an excellent course, taught by competent professors. I believe that in the main this course does very well in achieving its objective of knowledge transfer. However, having experienced it, there were parts where the professor was demonstrating a topic using a video presentation showing him operate a process or screen sequence on his computer. These aspects, like virtually all the material on this course, are of a technical nature and contain many important details. As such, to help complete and re-enforce their learning, students require something like a sequence of slides that they can print out and retain for revision and future reference. In certain parts, the provision of the printable screenshots in the form of slides was absent.

An important theme of the course and Data Science in general is "Reproducible Research". What I'm arguing for here is, "Reproducible Learning Materials" covering a complete course, not only parts of it. Admittedly, it was only a very small proportion of the course that suffers from this defect. But I would not like it to become the norm in the future. As a suggestion, it could be possible to author a lecture using HTML so as to combine the verbatum lecture text with every slide/screenshot image embedded in its right position within the lecture.

I notice Coursera courses have also moved away from the weekly lists of individual lectures together with their links to .txt, .mp4, etc. files. The new presentation keeps you submerged within the flow within each week's series of lectures. One has to 'click out' in order to watch your progress and then re-enter the lectures at a resumption point. I prefer the previous navigation structure in order to access lectures and materials. Printed learning materials are also important for me, in addition to the video lectures. The latter are of course vital as the medium for the initial exposure of the material.

Excellent content. I was expecting more examples related to the industry, such as data products for data journals, telcos, etc.