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Kursteilnehmer-Bewertung und -Feedback für Developing Data Products von Johns Hopkins University

4.6
1,853 Bewertungen
349 Bewertungen

Über den Kurs

A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creating data products using Shiny, R packages, and interactive graphics. The course will focus on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience....

Top-Bewertungen

SS

Mar 04, 2016

This is a great introduction to some of the many ways to present your data. It's probably the easiest course in the specialisation but shows off an impressive array of widgets and gadgets.

RS

Nov 19, 2018

This course was amazing, it could definetly be more deep in each of the subjects, but gives you so much practice in tools that are very useful in the day by day of a data scientist

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326 - 348 von 348 Bewertungen für Developing Data Products

von Michael K

Feb 13, 2016

Lots of material in a short amount of time.

von Aleksey K

Feb 26, 2016

The course is OK, but I'd rather learned app development with Python or Java.

von Martin S

Feb 26, 2016

Updated and entertaining!!

von chris

Oct 19, 2017

Good range of topics - updates to content would be useful --> eg http://jupyter.org

von Brandon K

Apr 06, 2016

The class was OK. This was the topic I was most excited to get to in the specialization, so I started playing around with Shiny, Slidify, and other tools ahead of time. Because I had gained some basic familiarity with those packages, this class was a bit of a letdown. I was happy with the week on making R packages. That was all new and fascinating. If you're looking for something more advanced than a very basic overview, you may want to look elsewhere.

von Marco S C

May 23, 2016

This module is not the same level as the previous ones, giving a superficial view of several package but not on any deepens. The application development was the positive part of the module.

von Léa F

Feb 19, 2018

This course is clearly not the most interesting of the specialization regarding math/theoretical knowledge, but it helps you get to know a nice way of presenting your results.

von Tai C M

Oct 07, 2017

Not bad. But I feel that this topic is more for those who likes to develop web products.

von Ytsen d B

Aug 15, 2017

From this course I took away how to make shiny apps.

This is very useful and fun to do.

There was much more material covered in the course, but that was not tested via the assignments.

That means that passing the course does not ensure that you actually master these subjects as well (one example is creating and publishing a new R package).

von Vitalii S

Sep 02, 2017

This course can be updated:

1) add swirl lessons.

2) add more video materials

von Vaibhav S

Nov 13, 2016

A bit fast paced as they teach so many things in a single week. But the stuff they teach is surely great and makes you appreciate the beauty of R

von Aaron W

Aug 29, 2018

The course is a great survey of tools for sharing data analyses with R. Unfortunately, the content is already a little out-of-date because the technology is always developing.

von Diego T B

Nov 07, 2018

Interesting but I had to learn most of the things here by my own

von Paul R

Mar 14, 2019

A disappointing end to the pre-capstone lectures, taking the foot off the machine learning gas from course 8 with a detour back to tools and yet another Rmarkdown lecture. This basically covers building shiny apps (needed for the capstone), leaflet (maps), making presentations in RStudio - then gets lost in R Packages and Swirlify which are not very useful here. Some of this is needed in the capstone, but this course can be compressed and combined with earlier courses and make room here for something more substantial at this late stage in the specialization.

von Lucicleyton H d F

Feb 06, 2019

The syllabus is very unbalanced through the weeks. For example the week 01 could be split into two weeks . The week 04, in my view, is unnecessary.

von Seth D

May 23, 2016

seemed like a filler, nit are why this was included

von Chuxing C

Apr 07, 2016

Would like to use the time to learn more machine learning/predictive technique, etc.

von Stefaan D

Oct 28, 2016

I am a developer and know how to create advanced websites. This course has less use for me as in my day job i create sophisticated websites

von Brian F

Aug 20, 2017

This was a fun course, but not particularly useful.

von Chan W Y J

Jan 17, 2018

peer reviewers are spastic mouth breathing idiots.

von Lazar K

Feb 14, 2017

I didn't learn many data science concepts in this class

von Stephen E

Jun 27, 2016

To be honest I don't think this is worth the money.

von Robert H

Jan 07, 2016

This review does not reflect the course content. The new Coursera UI makes it impossible to download transcripts or slides of the videos. Without these features, following the lectures is significantly more difficult, and I can't rate this course any higher than 1 star. I would rate it zero stars if that was possible.