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존스홉킨스대학교의 Reproducible Research 학습자 리뷰 및 피드백

3,441개의 평가
487개의 리뷰

강좌 소개

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....

최상위 리뷰


Feb 13, 2016

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.


Jun 23, 2017

Of course, I liked this course. There was even an extra non-graded assignment. Plus two graded assignments. Quality instruction videos and lots of practice. Everything a learner needs.

필터링 기준:

Reproducible Research의 470개 리뷰 중 1~25

교육 기관: Matthew S

Mar 05, 2019

I often feel like people completely ignore the "science" aspect of data science (read any data science career question on quora for example). This course does an excellent job of introducing key aspects of the scientific method that you might not have encountered if you've never done an experiment before. The final project is a lot of work (mostly data cleaning) but very fun and informative.

교육 기관: Dzmitry S

May 10, 2016

Too expensive for such a simple course

교육 기관: Chris M

Apr 09, 2016

I've already written a review but it seems to have been removed...

This is an awful course, there is very little purpose to it whatsoever, it is basically a module in markdown which will in all honesty not have much application for most learners.

In addition, the course is not at all balanced / laid out well, there is a peer assignment in week 1, which you need to have covered week 2's content for.

Lastly, the recording quality of some of the lectures is awful, it is clear that they have simply used some recordings of an actual classroom session of a related course instead of recording for Coursera.

In all honesty, this entire specialisation is of awful quality, it is not a data science course, it is a "here's a few useful things in R" course, and the instructors should be ashamed that their institution makes money from it.

교육 기관: Mahmoud E

Nov 27, 2018

Great course very informative

교육 기관: Chanpreet K

Dec 30, 2018

Good course content. All things explained quite well.

교육 기관: Anusha V

Jan 03, 2019

Excellent Course - particular useful for anyone doing research and performing any kind of analysis on the observed data.

교육 기관: Bruno R d C S

Jan 22, 2019

A great introduction to basics of scientific method concerning statistics and result reporting.

교육 기관: Azat G

Jan 24, 2019

Amazing course, it introduced the concepts of reproducibility which is used to provide scientific fairness, transparency.

교육 기관: Fidel S C

Mar 20, 2019

Very good course

교육 기관: Andrew

Apr 07, 2019

One of my favorite courses in the specialization so far.

교육 기관: Naren R B

Apr 08, 2019

Would definitey recommend this, it covers an important aspect of research for Data Scientists.

교육 기관: carlos j m

Apr 12, 2019

Great course, good lectures. I learned a lot of usable skills.

교육 기관: Glenn W

Mar 04, 2019

Favorite course so far. Really enjoyed working on the projects. They were very helpful in helping to reinforce the material.

교육 기관: Alzum S M

Jan 08, 2019

A great course that will take you ahead to be a Data Scientist

교육 기관: Carl W

Jul 10, 2018

Knitr was a nice tool to learn. I can see it being useful.

교육 기관: Aleksander Z

Apr 25, 2017

Quite good course.

교육 기관: 刘博

Mar 03, 2017

good work

교육 기관: Solomonov A

Jan 19, 2017

Great course. Make you think like a scientist.

교육 기관: Donald J

Jan 22, 2018

These are important skills for a data scientist and I'm glad there is a full 4-week course dedicated to reproducible research.

교육 기관: Ryan C Y H

Jul 02, 2017

Taught useful things!

교육 기관: Jose P

Feb 12, 2018

Perfect to aid past and present curation and validation of research. Thank you!

교육 기관: Vitalii S

Jun 27, 2017

I enjoyed this one so much! Give me more...

교육 기관: 陈颐欢

Jun 11, 2018

The concept introduced here is very essential and basic for high quality data analysis

교육 기관: George G A

Aug 20, 2017

Loved it! I am not as technical as others in my class, so I struggle a bit with the programming part. However, I understand the importance of and now how to perform Reproducible Research in an industry-wide format. The examples given in the videos, especially regarding medical studies gone awry, stress the importance of attention to detail and reproducibility.

교육 기관: Atair A C j

Oct 07, 2017

I was able to learn very good base to assure my work can be reproduced within my peers.