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Opiniones y comentarios de aprendices correspondientes a Developing Data Products por parte de Universidad Johns Hopkins

4.6
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2,110 calificaciones
393 reseña

Acerca del Curso

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....

Principales reseñas

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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76 - 100 de 392 revisiones para Developing Data Products

por Benjamin S

Nov 28, 2016

Love this course. Many interesting features (Shiny App, Maps, etc.) that I will definitely use for my job.

por Partha S G

May 08, 2017

I was a good exposure to data products building. Would be great to have something advanced on the topics.

por René S K

Apr 16, 2017

Thanks to these courses, I program production planning and control software for the company I work for.

por Lauren B

Mar 03, 2016

I loved learning how to build a Shiny application. I know this skill will serve me well moving forward.

por Raju G

Dec 11, 2017

Nice to learn making presentations & applications and hosting them on websites to share with the world

por Karthik R

Aug 07, 2017

Excellent Introductory course that provides good understanding of how to go about developing products.

por Srikumar G

Dec 26, 2016

very good course to understand on how to present your work in a very structured and repeatable manner.

por Francisco G

Jan 07, 2018

I would dedicate more time to shiny and reduce the time of number of lessons devoted to RMarkdown.

por Jared P

Jun 25, 2017

Loved this course. Would recommend it. I particularly enjoyed learning Leaflet and Shiny Apps.

por Vincent C

Oct 20, 2017

Good course on Data Products, I learned a lot about R Packages, shiny and the leaflet library.

por William R

Jun 12, 2017

Had issues with RStudio and the TA/coursera was great to work with and troubleshoot the issue.

por Giovanni V

Apr 10, 2016

I greatly enjoyed this course. It helped me to improve my skills in the field of data science.

por Avinash K

May 28, 2020

I feel well equipped for presenting statistical results after taking this course. Thank you!

por Evgeniy Z

Apr 12, 2016

Nice introduction which allows to start using some tools to present results of the analysis.

por Lei S

Jan 04, 2018

Very interesting course. I spent me a lot of time because I always want to try new things.

por Eric S

Jul 23, 2020

Great course. Covers a large range of topics, but is well-paced and easy to follow along.

por Raunak S

Nov 26, 2018

a very good beginner level course for those learning how to develop Data Products in R.

por Laro N P

Aug 15, 2018

Awesome course, maybe more complex examples, but is fine as an introductory program.

por Wei W

Nov 16, 2017

This is by far my favorite course among the 9 courses I took in this specialization.

por Rose G

Mar 31, 2020

All of the content was in the first two weeks, but really interesting nonetheless.

por Saah N T G

Dec 29, 2018

Awesome Lessons!

I learned how to build shiny application and today I'm very happy!

por Henri A

Aug 27, 2020

I enjoyed the course and especially the interaction of the results with Internet.

por Ignacio O

Mar 30, 2020

Its a very nice course to learn the basics on how to prepare an data science app.

por Glener D M

Jun 15, 2019

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

por Antonio F

Jun 25, 2016

Good introduction to a wealth of great tools and to the concept of data products.