Developing Data Products
★★★★★(58 customer reviews)
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8.3/10 (Our Score)Product is rated as #180 in category Data Science
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.
Brian Caffo, PhD is a professor in the Department of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health. He graduated from the Department of Statistics at the University of Florida in 2001. He works in the fields of computational statistics and neuroinformatics and co-created the SMART ( www.smart-stats.org) working group. He has been the recipient of the Presidential Early Career Award for Scientist ( PECASE) and Engineers and Bloomberg School of Public Health Golden Apple and AMTRA teaching awards.
Courses : 7
Brian Caffo, PhD
Courses : 7
Specification: Developing Data Products
58 reviews for Developing Data Products
4.7 out of 5
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Developing Data Products
Julien N –
discovery of amazing tools and possible applications of rstudio and additional packages. good pace of the course
Jesse K –
The concept itself was great, but there were numerous issues with the peer review exams, especially around the requirements.
Saah N T G –
Awesome Lessons! I learned how to build shiny application and today I’m very happy!
A lot of useful parts for visualization here! plotly and shiny are super useful in a business context. swirl and leaflet a bit niche perhaps.
Mohammad A –
Great course, practical and very informative
Lucicleyton H d F –
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.
Vijay B –
Review took too long
Daniel J R –
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.
Raul M –
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
Cesar A –
Demanding if you are not used to do this kind of things, but, worth It if you give yourself a time to get into it.
Paul R –
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.
Joao F –
Excellent course (like the previous 8 in the specialization) and very useful for anyone working with data and involved in data storytelling. Brian (the teacher) does an awesome job explaining the concepts and how the functions and scripts in R work and interact with each other to bring about shiny apps and other visualizations. A big “Thank you!” to everyone who created this course!
Alfredo A N –
Interesting course but some topics don’t have motivation
Premkumar S –
Great course!! Was very excited with the whole process of learning to write an app and create something useful!! Thank You!
Bruno R d C S –
this curious course teaches about tools and techniques for communication with audiences on data science. some tools are very interesting and deserve a deep research from the learner, this course is mostly informative about the potential of such tools.
Nino P –
In terms of practical data science in R, this is the most usefull course in the specialization. Here you can learn a lot about very important R packages such as shiny, MarkDown, leaflet,… Highly recommendable and very, very important.
Subramanyan K P –
Luis M M R –
Glener D M –
Indispensable for anyone who wants to make a career in data science. I recommend.
Jeffrey M H –
This course provided a great number of methods used to deliver a data project.
jessica c f –
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!
Ingrid T –
Best class of the specialization. The assignments were actually instructive.
Diego C –
John D M –
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!
Brayan A A X –
German R M S –
Excelente curso, 4 estrellas debido a que las instrucciones para revision no son tan claras y los companeros revisan de forma subjetiva.
Shubham K –
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.
Rodrigo F L L –
Excelent introduction to the topic and really fun to use!
Khalid S A –
Andreas P –
Thank you very much.
Rok B –
It is a very good course. There’s quite some work, but the content isn’t hard. Make sure you update your RStudio for all the features to work correctly
Manuel E –
Some parts could be dropped and devote that time to develop the content of others beyond scratching the surface.
Charbel L –
Very good. Basic but very diverse
Muhammad Z H –
Connor B –
great exposure to the tools available in R
Yogesh D –
Very good course from app development perspective
Rizwan M –
Alimohammad P –
Out of the other 8 modules, I personally liked this one the most. Here is where you put into practice what you’ve have learned so far. Great job guys!
Courtney R –
Great opportunity for applying what we’ve learned.
Robert J C –
Able to run app on line. Super.
Mehrdad P –
overall it was ok, but it is somewhat limited.
Wellintton P –
great course with a lot of hands on work
Eric J S –
I learned what I wanted to get through this class. I didn’t learn most of it in the class.
Purificacion V –
This course is as good as previous from Data Science Specialitation. Thank you!!
Claudio F S –
Excellent course! To learn how to build of App in R by using Shiny is differential for a Data Science Analyst.
Bolaji O –
It another great lecture in this specialization course. Simplified, understandable, and highly impactful. You’d learn A Z of shiny app development.
Yadder A G –
All that I learned on this course it’s totally helpful. I loved this course because I feel that learn a lot of new useful tools that I can use in my work.
Pedro M –
Heavy on boring videos!
Doug A –
It was a great class.
Amanyiraho R –
I wish there was a sixth star
Dr. T A –
I appreciated the wholistic approach of presenting the information via GIT, R shiney server and making the slides…. all very useful going forward.
Leonardo Z –
There are some concepts that should be disclosed as pre requisites for this course. I had to re sit this course not for the content but for the pre requisites.
Jose A N –
Great value and inspiring.
Ivan V M –
Good hands on!!!
Rob S –
You learn a lot of things that you can use also in other domains.
Ignacio O –
Its a very nice course to learn the basics on how to prepare an data science app.
Shailesh S P –
Rose G –
All of the content was in the first two weeks, but really interesting nonetheless.