Developing Data Products

Provided by:
5/10 stars
based on  3 reviews
Provided by:
Cost FREE
Start Date TBA

Course Details

Cost

FREE

Upcoming Schedule

  • TBA

Course Provider

Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4733 reviews

Course Description

Learn the basics of creating data products using Shiny, R packages, and interactive graphics. This is the ninth course in the Johns Hopkins Data Science Specialization.
Reviews 5/10 stars
3 Reviews for Developing Data Products

Ratings details

  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars

Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.

Sort By
Hamideh Iraj profile image
Hamideh Iraj profile image
8/10 starsCompleted
  • 70 reviews
  • 60 completed
5 years, 4 months ago
It was probably the best course on data specialization series. It is a tool- oriented demo like course about ways to create data products including R packages, shiny,R Studio Presenter,slidify and some other tools.  you can get a general overview of the products and learn those you need. For the course project you should do a shiny project and Rstudio Presenter or slidify on your choice. I do not agree with Richard in the idea that it is easy to learn them from web. It takes too much time and effort to select and gather  these stuff from the web and I appreciate the effort done by the instructors. It is not brilliant but I learned and enjoyed.
Was this review helpful? Yes1
 Flag
Greg Hamel profile image
Greg Hamel profile image
4/10 starsCompleted
  • 116 reviews
  • 107 completed
5 years, 5 months ago
Developing data products is the final course in the 9-part data science specialization offered by John Hopkins on Coursera. This course introduces several tools you can use to put R code on the web, into slideshows and into R packages, including Shiny, rcharts, Google Vis, slidify and R studio presenter.  Although the course is listed as 4 weeks it only has 3 weeks of lecture content, with one week devoted to giving students time to work on the course project. Unlike previous courses in the data specialization, this course is not taught by a single professor: each of the 3 professors involved in the data science specialization leads a few lectures. This course provides a decent overview of some useful tools for integrating R with the web and in presentations, but it covers too many different tools in too short a time without any exercises to help students practice using the tools presented. You'll have to spend a lot of time on your... Developing data products is the final course in the 9-part data science specialization offered by John Hopkins on Coursera. This course introduces several tools you can use to put R code on the web, into slideshows and into R packages, including Shiny, rcharts, Google Vis, slidify and R studio presenter.  Although the course is listed as 4 weeks it only has 3 weeks of lecture content, with one week devoted to giving students time to work on the course project. Unlike previous courses in the data specialization, this course is not taught by a single professor: each of the 3 professors involved in the data science specialization leads a few lectures. This course provides a decent overview of some useful tools for integrating R with the web and in presentations, but it covers too many different tools in too short a time without any exercises to help students practice using the tools presented. You'll have to spend a lot of time on your own exploring the tools discussed to really learn how to use them. It's nice to be aware of the kinds of tools that are out there and have some basic information on each one to get started, but in keeping with the theme of the entire data science specialization, coverage is only skin deep. Now that I've gone through all 9 courses in the data science specialization, I can say that on the whole, the data science track is disappointing. On the plus side, you will gain basic R proficiency if you complete the R programming, getting and cleaning data, reproducible research and exploratory data analysis courses. That said, too much of the material is poorly presented with a lack of instructor face time and overly cluttered slides. The courses routinely try to cover too much materiel too fast and skimp on content in the later weeks. There are no in-lecture quizzes and few interactive exercises or quality homework problem sets. A cynic might question John Hopkins' motivation in offering the data science specialization: making 9 short courses that they can rerun each month and charge $50 a pop to anyone interested in verified certificates smells a bit like an experimental cash grab. Regardless, there are several other MOOCs out there that cover the same topics better.
Was this review helpful? Yes2
 Flag
Richard Taylor profile image
Richard Taylor profile image
1/10 starsCompleted
  • 29 reviews
  • 28 completed
5 years, 4 months ago
This course is about writing web applications using R and Shiny. You are not going to learn anything here that you can't learn on the web if you need to use shiny. Just follow the shiny tutorial and you are good to go for the first quiz and the project. And that if is the big problem in this course. As a part of a specialization you are forced to learn a tool that has nothing to do with data science. The lectures are chaotic, jumping from topic to topic without a clear explanation of anything. After a few lessons the instructor uses cartoon animations which would be fine if the course would be aimed to children. These animations only make this course really sad, the time taken to produce the animations could have been used to create a good lecture and good examples about how to use shiny, how to do different things and show more examples. Shiny itself is quite a horribly done thing, the syntax is chaotic the way things are coded are ... This course is about writing web applications using R and Shiny. You are not going to learn anything here that you can't learn on the web if you need to use shiny. Just follow the shiny tutorial and you are good to go for the first quiz and the project. And that if is the big problem in this course. As a part of a specialization you are forced to learn a tool that has nothing to do with data science. The lectures are chaotic, jumping from topic to topic without a clear explanation of anything. After a few lessons the instructor uses cartoon animations which would be fine if the course would be aimed to children. These animations only make this course really sad, the time taken to produce the animations could have been used to create a good lecture and good examples about how to use shiny, how to do different things and show more examples. Shiny itself is quite a horribly done thing, the syntax is chaotic the way things are coded are very dirty and the results look very bad. For web development there are really much better tools. A bad course for a bad tool that I hope you don't ever need.
Was this review helpful? Yes2
 Flag

Rating Details


  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars

Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.