Opiniones y comentarios de aprendices correspondientes a Reproducible Research por parte de Universidad Johns Hopkins

Reproducibility is one of the key elements of modern scientific method. The course was very informative and introduce ideas I did not know before, but are crucial.

This course helped me realize why reproducible research is absolutely necessary, and gave me the tools to implement reproducibility in my work. Project was great.

A good informative course to inform about importance of "Reproducible Research", also a good one for practicing code writing and publishing in RPubs and Github.

This class's R markdown material taught me to efficiently convey and market data analysis to non-specialists of data. It was immediately valuable to my career.

Good info on RStudio & RR.

I can easily figure out who has attended this course by their methodical nature and work when I see Kaggle competitions. Great job!

A handy course to do when you have to create and submit reports with calculations and code. Learn the basic principles of report writing and report structure.

Though I could not solve all course projects on my own, I at least understood the techniques and enjoyed doing the course greatly. Thanks to the instructors

I found all the topics of this course important. Not only for my professional career but also for everyone who is involved with data and science in general.

Very important course. Not so many fancy analysis but it introduces to Markdown and explains well what does it mean to do data science within a community.

a very important part of data analysis. I especially found the case study in week 4 to be of tremendous interest highlighting the real world applications.

Great course. This and the previous course in the data scientist specialization are extremely practical and I've found immediate utility in my career.

Very interesting, the fact that our research procedure can be explained and showed to other to reproduce, validate and work on top of it is fantastic.

Very useful in bringing together skills learned in the earlier courses of the Data Science specialization: R programming, R Markdown, knit, RPubs.

Very important subject matter taught well. My only qualm is that the final project was more difficult than I expected it to be given the content.

Good course. Examples given throughout the course are biological based so it is little hard to understand completely because they are technical

this course is incredibly useful!

in my job i practice data analysis everyday and this course helped me to do everything in a more efficent way!

Excellent content and plan. The delivery is fantastic and the professor's explanatory clarity is top notch. I highly recommend this course.

Slightly less information than the previous courses in DS spec but important for someone who has not done scientific research in the past.

Excellent course that is both well presented and very clear, providing many examples and opportunities to practice throughout the course.

Very interesting course, I was able to apply what I learned in the previous courses of the specialization, and that was a good exercise.

Nice course! It helped me to understand the concepts of markdown and related R modules. The assignments were challenging and fun to do.

To be a data scientist you must use RMarkDown. Here you learn how to use it. A must do course for data scientists and highly valuable.

Thank you so much. Representatives lessons in my opinion very effective. I learn so much about html and markdown files in this course.

One of my favourites. The course is easy to follow and the idea of having a self-contained and reproducible document is very powerful.

It was a good experience. The final project has been the most challenging that I have had in the specialization, but I learned a lot.