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Reproducible Research に戻る

ジョンズ・ホプキンズ大学(Johns Hopkins University) による Reproducible Research の受講者のレビューおよびフィードバック

4.6
4,113件の評価

コースについて

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This course will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results....

人気のレビュー

AA

2016年2月12日

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.

RR

2020年8月19日

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."

フィルター:

Reproducible Research: 76 - 100 / 580 レビュー

by Pierre S

2017年4月11日

I think this not a complicated course but is absolutely fundamentals of proper scientific principles which are so often lacking in many data science/analytics projects.

by Juan P L R

2020年9月25日

Great course to learn about reproducible research in R, using knirt and RPub. Excellent course and carefully designed to complement the Specialization of Data Science.

by Tseliso M

2017年11月11日

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.

by Christian H

2016年11月10日

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.

by Himanshu R

2018年1月25日

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.

by Joshua B M

2016年3月4日

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.

by Subramanya N

2017年12月12日

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!

by Johann R

2017年6月7日

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.

by RR A I

2020年9月22日

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

by Camilo Y

2017年1月10日

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.

by Andrea G

2020年5月11日

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.

by Devanathan R

2016年2月7日

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.

by Charles M

2019年4月25日

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

by Marco I

2018年9月20日

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.

by Jessica R

2019年8月11日

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

by Arturo P

2021年6月22日

A relly nice course, it is not really difficult at all but it's really useful overall for researchers and making reports, i recommend it so much.

by Connor G

2017年8月30日

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.

by Praveen k

2018年10月18日

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

by Marco B

2017年12月5日

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!

by Charly A

2016年11月26日

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

by Warren F

2016年8月16日

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

by Prairy

2016年3月17日

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

by Tine M

2018年1月22日

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

by Anirban C

2017年8月15日

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

by Nino P

2019年5月24日

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.