Chevron Left
Вернуться к Воспроизводимое исследование

Отзывы учащихся о курсе Воспроизводимое исследование от партнера Университет Джонса Хопкинса

4.6
звезд
Оценки: 3,953
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:

201–225 из 547 отзывов о курсе Воспроизводимое исследование

автор: Lei S

27 дек. 2017 г.

Only thing: maybe some lectures should be updated.

автор: phani v k

7 янв. 2017 г.

This is a very good course for a begineer like me.

автор: Laro N P

2 мая 2018 г.

Good course. Every new course is a new challenge.

автор: Shivanand R K

21 июня 2016 г.

Great and Excellent thoughts and course material.

автор: Mickey K

18 авг. 2020 г.

Great course. very important for any researcher.

автор: Nguyen T T

8 мая 2017 г.

The course very good for beginner data scientist

автор: ILLYA B

12 окт. 2020 г.

The best course of John Hopkins Specialization!

автор: Akram N

2 мая 2019 г.

Very fruitful. I enjoyed this lesson very much.

автор: Jamie M

26 окт. 2018 г.

Good course. Does exactly what it says it does.

автор: Utku K

14 нояб. 2016 г.

Good lesson, about an interesting topic for me.

автор: Predrag M

13 мар. 2016 г.

One of the best courses in this specialization.

автор: Bipin K

10 февр. 2016 г.

great one to know how about researches are done

автор: Leonardo R d L P

29 июля 2020 г.

Excelent, very straight foward and informative

автор: Lingareddygari U R

30 июня 2020 г.

A must course for any data science enthusiast.

автор: Martin D

28 окт. 2018 г.

Great course, great lecture and great content.

автор: Solomonov A

19 янв. 2017 г.

Great course. Make you think like a scientist.

автор: Hemanth P M

16 мая 2016 г.

good course. I will recommend it for everyone.

автор: Anil G

14 мая 2018 г.

One of the best learning contents, great cour

автор: Harsha v s p B

10 окт. 2020 г.

Amazing course so far in the specialization.

автор: Javier E S

20 мая 2018 г.

Excellent course. A lot of issues to learn .

автор: ooi s m

10 июня 2017 г.

detailed explanation with practical hands-on

автор: Blaž Z

27 авг. 2019 г.

Very nice project at the end of the course!

автор: Changkeun K

1 авг. 2017 г.

very useful and challenge but so memorable.

автор: Vitalii S

27 июня 2017 г.

I enjoyed this one so much! Give me more...

автор: Connor B

19 авг. 2019 г.

Course Project 2 was fun and learned a lot