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Отзывы учащихся о курсе Воспроизводимое исследование от партнера Университет Джонса Хопкинса

4.6
звезд
Оценки: 3,947
Рецензии: 564

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
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.

RR
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:

151–175 из 547 отзывов о курсе Воспроизводимое исследование

автор: Talant R

24 окт. 2016 г.

Great course to learn "knitr" and how to code in reproducible manner!

Totally recommend it!

автор: Eric K

21 июня 2020 г.

Excellent course. Roger Peng is a fantastic instructor and knows R and data science well.

автор: Giovanni V

10 апр. 2016 г.

This course helped me to apply skills learned in the other courses of the specialization.

автор: Georgios P

31 окт. 2018 г.

I learned how to write and publish reproducible articles in a very short period of time!

автор: Juliana C

25 сент. 2017 г.

Great great course to learn basics on reproducibility, and nice R tools like R Markdown

автор: Wassim K

26 мая 2017 г.

I enjoyed it a lot. the learned material is applicable to any scientific work to be done

автор: Atair A C j

6 окт. 2017 г.

I was able to learn very good base to assure my work can be reproduced within my peers.

автор: 陈颐欢

10 июня 2018 г.

The concept introduced here is very essential and basic for high quality data analysis

автор: Rob S

6 февр. 2020 г.

very interesting, but a pity about the errors that occur due to incompatible software

автор: Shubham S

24 нояб. 2019 г.

Thank you instructors, for making me realize the importance of reproducible research.

автор: Rodney A J

6 июля 2017 г.

This is a great course on a very important topic that every researcher should master.

автор: Lindy W

18 дек. 2016 г.

Learnt some really neat new tools. Favourite course from this specialisation so far.

автор: Stephan H

9 окт. 2017 г.

Nice course. But I'm always worried about the estimated lengths of the assignments.

автор: Brendan M

28 февр. 2017 г.

This was possibly the most important class I took, which was completely unexpected.

автор: Sai S S

27 июня 2017 г.

Think an assignment after week-3 even if its a fishing expedition would add value.

автор: Raunak S

11 окт. 2018 г.

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

автор: Frederik C

29 мая 2018 г.

Key aspect for a good data scientist. It was a nice introduction to knitr etc...

автор: Jose P

11 февр. 2018 г.

Perfect to aid past and present curation and validation of research. Thank you!

автор: Emil L

3 нояб. 2016 г.

Great Course, should be free to all freshman graduate students across the world.

автор: Jim M

22 мая 2020 г.

Very nice final course pulling everything together from the previous 4 courses.

автор: Nilrey J D C

7 окт. 2019 г.

A very good course to know why it is important to have a reproducible research.

автор: xuwei l

15 мая 2016 г.

excellent course to introduce practical approach for reporting data analysis !

автор: Harland H

1 июля 2018 г.

Very informative. Will use this on the job to make producing products easier.

автор: SATHYANARAYANAN S

10 сент. 2017 г.

Very good for anyone wanting to get into the field of Data Science using R

автор: Anita M G

5 авг. 2020 г.

Thank you So much !!!

This course wonderfull.. Learnt so many new things.