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Avis et commentaires pour l'étudiant pour Recherche reproductible par Université Johns-Hopkins

4.5
3,318 notes
469 avis

À propos du cours

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....

Meilleurs avis

AA

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.

AS

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.

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1 - 25 sur 454 Examens pour Recherche reproductible

par 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.

par Dzmitry S

May 10, 2016

Too expensive for such a simple course

par 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.

par Anusha V

Jan 03, 2019

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

par Omar N

Nov 08, 2018

Really good module/course, gives you a glimpse into real world implementation of data science and the challenges involved with it.

par Premkumar S

Nov 12, 2018

Excellent course! Very good course materials and well thought out quizzes! Highly recommend!!

par Mahmoud E

Nov 27, 2018

Great course very informative

par Alzum S M

Jan 08, 2019

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

par Bruno R d C S

Jan 22, 2019

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

par Azat G

Jan 24, 2019

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

par 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.

par Fidel S C

Mar 20, 2019

Very good course

par Chanpreet K

Dec 30, 2018

Good course content. All things explained quite well.

par Nicholas S

Nov 16, 2018

Great course!

par Md G M

Jul 30, 2018

Course contents are very good and easy to understands.

par Mohammad A

Jul 20, 2018

Great course , very informative and well organized

par Baburaj V

Jul 20, 2018

Nicely explained topics.

par Rodrigo A d S R

Sep 05, 2018

Really cool concept and pratice

par Raunak S

Oct 11, 2018

great course for those wanting to learn basic concepts of Reproducible Research.

par Akshay D

Oct 14, 2018

Great Experience..!

par Praveen k

Oct 19, 2018

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

par Marco A I E

Sep 20, 2018

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.

par Claudio F S

Sep 21, 2018

The course was fantastic. I realized the power that a Data Science Analyze can create. In this module in particular, I was even more interested in completing the specialization. Thank you Professor Roger Penn and the entire team of teachers for their teachings.

par Shashwat K

Sep 11, 2018

great course

par AKIL H

Oct 06, 2018

Coursera is best platform for E_Learning's