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Kursteilnehmer-Bewertung und -Feedback für Reproducible Research von Johns Hopkins University

4.6
Sterne
3,776 Bewertungen
542 Bewertungen

Über den Kurs

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....

Top-Bewertungen

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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76 - 100 von 525 Bewertungen für Reproducible Research

von Johann R

Jun 07, 2017

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.

von Camilo Y

Jan 10, 2017

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.

von Andrea G

May 11, 2020

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.

von Devanathan R

Feb 07, 2016

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.

von Charles M

Apr 25, 2019

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

von 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.

von Jessica R

Aug 12, 2019

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

von Connor G

Aug 30, 2017

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.

von 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

von Marco B

Dec 05, 2017

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!

von Charly A

Nov 26, 2016

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

von Warren F

Aug 16, 2016

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

von Prairy

Mar 17, 2016

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

von Tine M

Jan 23, 2018

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

von Anirban C

Aug 15, 2017

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

von Nino P

May 24, 2019

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.

von Keidzh S

Apr 24, 2018

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

von Leandro F

Feb 28, 2017

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

von Arjun S

Aug 27, 2017

Great stuff. Glad to have the course make us create an Rpubs profile and publish research. Recommended strongly for data scientists

von Daniel C J

Nov 14, 2016

Great course. A must for every analyst for its simple tips on reproducibility, which can go a very very long way at work or school

von 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.

von ONG P S

Jan 19, 2020

Very practical and knowledge learned can be applied into my works as auditors. This can benefit any fields involving using data.

von 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.

von Richmond S

Sep 29, 2016

I struggled in getting the final project right but it helped me understand the course better. Thumbs up reproducible research

von PRAKASH K

Jul 13, 2020

I strongly recommend this course ,it focuses on reproducible research which is equally an important aspect of data analysis.