Chevron Left
Вернуться к Воспроизводимое исследование

Отзывы учащихся о курсе Воспроизводимое исследование от партнера Университет Джонса Хопкинса

4.6
звезд
Оценки: 3,902
Рецензии: 557

О курсе

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....

Лучшие рецензии

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.

RR

Aug 20, 2020

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."

Фильтр по:

101–125 из 540 отзывов о курсе Воспроизводимое исследование

автор: 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

автор: 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.

автор: 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.

автор: 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.

автор: 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

автор: PRAKASH K

Jul 13, 2020

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

автор: 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.

автор: Amanyiraho R

Jan 13, 2020

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

автор: Azat G

Jan 24, 2019

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

автор: Anusha V

Jan 03, 2019

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

автор: Adrielle S

Apr 03, 2016

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

автор: 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!

автор: 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.

автор: 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.

автор: Lee Y L R

Feb 02, 2018

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

автор: 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.

автор: 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.

автор: Courtney R

Oct 07, 2019

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

автор: Thiago

Aug 12, 2019

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

автор: 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.

автор: 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 ¡¡

автор: Jared P

Apr 10, 2016

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

автор: Suryadipta D

Apr 12, 2018

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

автор: Marco C

Feb 25, 2018

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

автор: santiago R

Nov 29, 2017

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