par Christopher M P•
30 mars 2020
Course is half-dead. Uses peer-review, but not enough peers to review assignments. Had to wait two months for grade on final assignment.
par Min P•
30 juin 2020
The most painful process of this course including previous ones except the first one is to wait for assignments to be graded.
Although you would get them done eventually, the process is needlessly painful.
While I'm content with the hands-on experience from visualizations to packaging in R, I hope the course be more learner-friendly environments.
par Christopher M T•
20 août 2019
Very good course. The topics are interesting and relevant to anyone who wants to learn more about development, specifically about data science tools. The courses do require a lot of outside reading and research to complete the assignments though. While this likely mimics what one face in the day-to-day world on the job, there is an opportunity to fold more of this material into the course material itself. Overall, strongly recommend.
par Tim S•
28 févr. 2018
It really sucks to wait that long for grades.
par Maurizio C•
12 oct. 2017
Great gap between teaching and what is required to pass the course. Unnecessarily difficult. Not recommended.
par Sandjaja B•
6 juil. 2018
The exercise really summarizes pretty much what we have learned in the past 4 courses. It's justly designed to be challenging enough, but not too burdensome. This certification provides all the building blocks of data analysis and software development in R, data presentation and packaging for distribution and collaborative works. If combined with another certification in data science and machine learning, they would make a formidable offering to any candidate who wish to try a career in data science/data analysis field. Thank you Coursera, Roger and Brooke.
par Aditya G•
17 mars 2018
Exceptional Course ! :)
1 mai 2017
par Ioannis O•
20 avr. 2020
This course is excellent! I truly learned a lot about software development with R. The only problem is that it is open a few times a year, due to the small number of participants.