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

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3,775 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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101 - 125 von 525 Bewertungen für Reproducible Research

von 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.

von Amanyiraho R

Jan 13, 2020

Very interesting and tackles a very important issue that Data scientists always miss-out, reproducibility of your project

von Azat G

Jan 24, 2019

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

von Anusha V

Jan 03, 2019

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

von Adrielle S

Apr 03, 2016

Muito completo. Inglês claro. Muitos exemplos. Chega a ser repetitivo em algumas aulas mas, antes sobrar do que faltar!

von Krishna B

May 30, 2017

towards the end of week 1 lectures we can see all the parts of this specialization coming together in a very nice way!

von Prem S

Aug 02, 2017

Nice course,especially it gives you a general idea and foundation on r markdown files if you already know R studio.

von Federico A V R

Jul 27, 2017

This topic is relevant to the field, yet few institutions offer courses on it. Great knowledge, highly recommended.

von Lee Y L R

Feb 02, 2018

Clear sharing of the importance of having proper documentation of data analysis process to enable reproducibility.

von Ann B

Mar 14, 2017

I think this topic is sometimes overlooked, but very necessary. This course did a good job of covering the topic.

von Emily S

May 18, 2016

I think this is an essential course that more people should take. Reproducibility is a huge issue in many fields.

von Courtney R

Oct 07, 2019

I really appreciated the topics covered in this course. Is a wonderful follow-up to the Exploratory Data course.

von Thiago

Aug 12, 2019

course material and projects help a lot in learning and tips on how to better document research and projects

von Gregorio A A P

Aug 26, 2017

Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.

von César A C

Jun 05, 2017

I really needed this course to fully understand how to work with R from the raw data to publication. Nice ¡¡

von Jared P

Apr 10, 2016

Loved it. The concepts around reproducible research are important. Should be mandatory teaching in school.

von Suryadipta D

Apr 12, 2018

well organized and easy-to-understand subject material, shapes up really well towards the specialization.

von Marco C

Feb 25, 2018

Very useful course to build a scientific way of thinking, and publishing my work has been very engaging.

von santiago R

Nov 29, 2017

Very nice course. R Markdown make everything looks better and understandable for a reproducible research.

von Yasel G S

Aug 04, 2016

This course was very important for my work. I learned so much and I want to say thanks to the professors.

von Shreyas G M

May 01, 2016

Excellently designed course! I loved how the course content and assignments were designed and delivered.

von sneha

Apr 16, 2018

the best course I have ever come across which gives us an idea about knitter and markdown packages in r

von Mauricio V

Dec 13, 2016

excellent course, specially all the topics related to markdown, rpubs. A must for each data scientist.

von Timothy M S J

Nov 29, 2016

Great class. It helps frame all that you will do as a Data Scientist. Building blocks. Peng nails it.

von Edwin L A

Aug 13, 2017

Excelente, sigo en el proceso muy animado y trabajando duro, ha sido una experiencia muy importante.