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.
About this Course
학습자 경력 결과
공유 가능한 수료증
완료하는 데 약 12시간 필요
학습자 경력 결과
공유 가능한 수료증
완료하는 데 약 12시간 필요
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
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DEVELOPING DATA PRODUCTS의 최상위 리뷰
Nice course and good classmates. It's very focus oriented and gives very good idea of Shiny, Rmarkdown, plotly and how to publish documents on github, Rpubs and other online sites. I learnt power of R
Compared to the other classes in the JHU Data Science specialization, this one is pretty laid back. It's useful information, and teaches a few nice tricks on how to present data analysis results.
This course lacked required information of help to get started. Now thanks to some posts by mentors i was able to successfully complete the Capstone project. Overall a very good experience!
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.
Interesting topic, touching on many field. I believe it was quite informative as it applies on the previous modules knowledge into this one. However it didn't touch deeper on each topic.
Good overview of available tools. Lack of practice exercises makes preparing for quizzes difficult. However, the course project does a good job to get your feet wet with Shiny Apps.
Good course, but I felt it was a bit easy to get good marks on the assignments with a minimum effort assignment. Some of the ones I marked were very little to do with data-science.
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
Course content was helpful. Some confusion in assignment questions not aligning with what was covered in lectures where it would have helped to clarify that was intentional.
very helpful and teaching. learning practical tools for producting data products. examples in the course are not very complex, but give a very good intro for several tools.
Although it is an easy course to pass, it is very important in content. It teaches the finishing moves, the ones you'll need after all your hard work. 5-star without doubt.
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.
The course not only instroduce me to great resources it also pointed me in the right direction to further develop the skills needed to create data products.
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.
It is a good course provide neccessary stuffs for data science.\n\nYou can skip week 4 as it is done previously in other courses . Small and good course.
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
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!
I appreciated the wholistic approach of presenting the information via GIT, R shiney server and making the slides.... all very useful going forward.
It another great lecture in this specialization course. Simplified, understandable, and highly impactful. You'd learn A-Z of shiny app development.
good class for beginners / teaches all good aspects of SQL and how to think critically at the end... which is what businesses want these days :- )
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