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Вернуться к Воспроизводимое исследование

Отзывы учащихся о курсе Воспроизводимое исследование от партнера Университет Джонса Хопкинса

Оценки: 4,045
Рецензии: 577

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

12 февр. 2016 г.

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.

19 авг. 2020 г.

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:

426–450 из 559 отзывов о курсе Воспроизводимое исследование

автор: Brian F

8 июля 2017 г.

Although there is not a lot to this course I like that it covers an area that is often neglected.

автор: Jeremy J

11 сент. 2016 г.

Some of the material seems pretty rote but it did introduce some new software and capabilities.

автор: Luiz E B J

21 окт. 2019 г.

This is a good course tht open our minds and eyes to the relevance of Reproducible Research.

автор: Joseph F

13 янв. 2021 г.

Now I appreciate what is the importance of a reproducible research! Awesome course overall!

автор: shivangi p

3 авг. 2020 г.

It is a nicely structured course with introduction to R and gives a brief of data science.

автор: Francisco M R O

9 мар. 2019 г.

It was very useful for me, now I know the importance of making data analysis reproducible.

автор: Korwin A

6 февр. 2016 г.

Great class with excellent supporting material. A little chaotic, but very good overall.

автор: Amol M

18 мая 2020 г.

This course provides an easy way out to create reports which can be shared with others.

автор: Thej K

12 мар. 2019 г.

Nothing serious in this course! Rmd is a good tool to work with! and get familiar with!

автор: Jean-Philippe M

30 июня 2019 г.

Lack of practical cases. The two cases are not really interesting and lack of details.

автор: Jaunius S

16 июля 2018 г.

The final task can be interpreted too widely. Do I need to pre-clean fuzzy data?

автор: Freddie K

16 апр. 2017 г.

Great course! Starting to put pieces from earlier courses together into a whole.

автор: Tim j

5 апр. 2017 г.

decent course, it is as long as you make it but start the final project early

автор: Eduardo S B

27 нояб. 2019 г.

The course is nice. However, I think the last assignment is simply too much.

автор: Sanjay J

6 мар. 2017 г.

I think it is one of the easiest and most important courses in Data science.

автор: Huw H

30 окт. 2017 г.

An interesting course on a topic that often doesn't get a lot of attention.

автор: Thomas G

30 нояб. 2016 г.

quite redondant with what was done before but very usefull and clear course

автор: Pieter v d V

20 мая 2018 г.

Nice to have seen once. Could have been condensed into two or three weeks.

автор: Herminio V

13 сент. 2016 г.

Very useful material, and great use for presenting data analysis results.

автор: Savitri

28 янв. 2019 г.

Nice and the content of the course will help you a lot to work on

автор: Ashish S

17 мая 2016 г.

This would be very effective for my personal skill enhancement.

автор: Ankush K

8 янв. 2018 г.

It's a great course on a topic that is not addressed enough.

автор: Kennan Y

13 июня 2017 г.

More details are needed about the R/knitr specific details

автор: Juan G

27 мая 2020 г.

Nice Course, it teaches R Markdown with RStudio and Knitr

автор: Angel M

11 мар. 2021 г.

Nice course about how present data and make reports.