My favorite course, at least it gives me an argument why scripted statistics is awesome and can be applied to a number of data related activities. Recycling chunks of code has proven useful to me.
A very important course that greatly improved my ability to communicate the findings of any sort of data analysis that I perform. This is a critical skill to acquire to "deliver the means."
por zhao m•
por manoj k•
por Chandan K S•
por �SADHARAN G•
por Rizwan M•
por SriHari a•
por Amit K R•
por Jay B•
por Yi-Yang L•
por Oleksandr F•
por Meidani P•
por Marat G•
por Jeffrey P•
By far the most time consuming, yet rewarding course in the data science specialization thus far. Literate Programing in general and R Markdown in particular are simple enough as concepts, but do take some time to grow accustomed to. However, I found the course to be a compelling argument for reproducibility that has application beyond just Data Science proper.
Although the technology is completely different, the concepts behind reproducibility really resonated with me and the work I do managing a division in Application Development. I'm constantly having to balance seemingly limitless demands, limited resources, and the difficulty of retaining staff in highly-competitive industry. Reproducibility becomes not just the basis for cross-training, product stabilization, and growth, but is a necessary ingredient of a team's survival.
This course not only cemented my own thoughts on the topic, but gave me some new ideas and tools for process improvement on the job.
por Nicolas L•
El proyecto final del curso tiene poco que ver con lo enseñado a lo largo de éste, era muy necesario haber tomado los cursos anteriores (en especial R programming y Exploración de Datos). Además, el proyecto debería estar mejor planificado, se buscaba que la mayor parte del tiempo estuviera en limpiar la data? O un objetivo más fuerte era el uso de gráficos más elaborados u otro al interior de RMarkdown? O un análisis un poco más elaborado que sólo sumar?
por Siying R•
This course teaches how to present a R code analysis that others can run the code to reproduce the same result. The length of the lecture is minimum and the project helps me to make the reproducible analysis on my own. One thing I would like to see improvement is that the instructor's speech. I hope that he can speak more smoothly without stopping to repeat words. It was quite a struggle to listen to his talking. Thank you.
por Travis M•
The first assignment should occur during the second week instead of the first given how the material is presented. The second and final project is very time consuming. Ideally this course should run for 6 weeks instead of 4 because of this. The second project is challenging and it definitely drives home the point about reproducible result given the state of the raw data.
por David R•
I don't think the content of this course was as polished as the others in the specialisation, the lectures seemed to be a mixture of repeats and videoed lecture room talks, based on content I'd probably have given 3 stars, however the 2 course projects, which were quite challenging given lecture content pulled it up, I found these very worthwhile.
por Erik A•
The concept is very important, so it's good that this course is available. The video's are sometimes not that great of quality. It's okay to show recordings of lectures, but the sound is of less quality.
Another thing is that the teacher says a lot of "euhm". I know he cannot help that, but once you notice this it becomes a bit annoying.
por Charles K•
Pretty good course that introduces a lot of useful tools and the concept of reproduciblity. However, it is not quite as applicable as the previous courses for those who are individual contributors in the private sector and rarely have others double check their analyses or need to publish anything.
por Felipe P•
In this course, there was a slide presentation with audio recorded in a classroom. This part of the course should be replaced as soon as possible to offer better experience. As it is presented right now, with a loudy environment, it really doesn't match to the quality of the other courses.
por Werner S•
Besides the "real" scientists like medicine or bioscience, I think the whole community would be better off it everybody would follow the principles laid out here: Do your analysis but make sure that others can follow the rationale and that your steps are documented and thus reproducible.
por Jose P M L•
This is a very useful course, it shows how to search your research in a complete manner. This is very important and even though its an easier course, the idea is important. The audio in the lessons that are taken from professor Peng real classrom is deficient. Its hard to keep track
por Bernie P•
Good theory course. As someone who holds a masters and worked through half of a PhD it wasn't super useful for me personally since I was aware of the power and need for reproducibility. It's not worth while but having more of a business use case for the need might be helpful.