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Вернуться к Сбор и сортировка данных

Отзывы учащихся о курсе Сбор и сортировка данных от партнера Университет Джонса Хопкинса

Оценки: 7,882
Рецензии: 1,294

О курсе

Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data....

Лучшие рецензии

2 мая 2020 г.

This course provides an introduction of some important concepts and tools on a very important aspect of data science: cleaning and organizing data before any analysis. A must for any data scientist.

1 февр. 2016 г.

Easy, mostly instructive Course. The Assignments and quizzes are quite good, and illustrates the lessons very well.\n\nSee the videos for general presentation, but use the energy on the excersizes.

Фильтр по:

1201–1225 из 1,258 отзывов о курсе Сбор и сортировка данных

автор: Joseph S

14 мая 2020 г.

This course has a very interesting subject and a concise syllabus, but is very poorly prepared. I hope coursera will pass on the message to Johns Hopkins University!

автор: Albert B

14 авг. 2016 г.

Too difficult practical exercises with the theorical background given. I know that hackers skill should be used but it is too much assumption in the projects!!

автор: Seyed A T

19 июля 2016 г.

It is somehow just an extension on R Programming course, with many unnecessary details that will be forgotten in a few days after the course.

автор: Sergio C d F

23 авг. 2016 г.

The video is simple and good.

But the final project and some test are too hard based on material presented.

Also staff's support are not good.

автор: Cintia K

9 мар. 2021 г.

Unfortunately the course's lectures are quite outdated, so you won't pass week 1 without all the research done by yourself.

автор: Ruwaa I

18 авг. 2020 г.

I learned "ask Google" and dplyr, nothing more. Not as satisfied as with the other courses in the specialization.

автор: Gianluca M

19 сент. 2016 г.

The only interesting part was dplyr. The rest was too confusing, with lots of lists and no explanations.

автор: Adam M

17 янв. 2020 г.

The information in the lectures is very stale, which makes it extremely frustrating to learn from.

автор: DESIREE P

10 мар. 2021 г.

Messier than the 2 previous courses. Lacks explanations for codebook in the peer-graded exam.

автор: Sudarshan P

5 дек. 2017 г.

The course material needs update. There are code snippets that do not work.

автор: Aditya D

18 сент. 2017 г.

This course could have been better. It was all textual and it got boring.

автор: James C

29 мая 2017 г.

Final assignment is not well detailed, and may cause confusion.

автор: Guy P

3 мар. 2016 г.

This course lacks projects to implement the skills we learn.

автор: Lee D

18 мая 2016 г.

The course was a bit mixed in terms of its quality.

автор: Colin H

21 окт. 2020 г.

Guidance for assessments could be a lot better

автор: Adam K

25 авг. 2019 г.

Very poor instructions for assignments.

автор: Rafee S

25 февр. 2019 г.

waste of time for software engineers

автор: Maximilian P

11 июля 2018 г.

Too many things in one place

автор: Sergio B S

17 нояб. 2017 г.

Worst class in this series.

автор: Michal K

29 апр. 2016 г.

too superficial

автор: Leandro J G D

12 мая 2020 г.

Lacking focus.

автор: Warren

5 авг. 2016 г.


автор: Walson Q

29 нояб. 2018 г.


автор: Dan H

16 янв. 2018 г.

This course is about getting data from the web and processing it using a computer language and packages in that language that are under active development. There is a github repo with course content and other electronic resources that are made to be easy to update. It has never been updated, even once since the course first went live 4 years ago. There are many broken links, several new features and bugs in packages that make lecture content obsolete or broken, errors found by students, etc. None of these issues have been addressed, even once, in any of the material, including the extremely easy to update content on github. This is disappointing and not very professional. Additionally, many of the notes are not particularly good to begin with. Much of it is essentially cribbed from other online tutorials, examples in the documentation, and in a few cases, someone else's (also broken) lectures. Take this course if you want a study group (the forums are actually quite useful) to help you go through 4 year old lectures rehashing online tutorials from 4 years ago about a topic that changes pretty quickly.

автор: Grant I

22 янв. 2018 г.

Made it all the way to week four and decided to drop this entire specialization. The data set in the final project is poorly referenced (despite the code book provided). The data set comes in 24 text files you have to merge (which isn't a problem in R) but what is a problem is when you don't understand what the variables and observations are. Perhaps if I worked in the medical field these measurements would mean more, but to a business major, they are incomprehensible with the limited documentation provided. So my assumption was, if I am having difficulty understanding what the final data structure should look like, others will be having the same problem......and its peer reviewed. How can I possible grade someone else