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Avis et commentaires pour d'étudiants pour Obtenir et trier des données par Université Johns-Hopkins

4.5
étoiles
7,938 évaluations
1,314 avis

À propos du cours

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....

Meilleurs avis

HS

2 mai 2020

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.

BE

25 oct. 2016

This course is really a challenging and compulsory for any one who wants to be a data scientist or working in any sort of data. It teaches you how to make very palatable data-set fro ma messy data.

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826 - 850 sur 1,277 Avis pour Obtenir et trier des données

par Rok B

15 mai 2019

The course has valuable content, but there is not enough emphasis on how to create a tidy data set. You kind of learn what a tidy data set is (although the definition is vauge), but you would need to see examples of messy data sets and how to convert it to tidy data set. There is one exercise in swirl called tidyr that addresses that, but it would be nice to have also videos on this topic.

par Ingrid M V

23 déc. 2020

Compared with other courses in the same series I observed several problems:

1. The explanation was not good, I had so many doubts that I clarified in other forums. The APIs lecture was too easy compared to the required to solve the quiz. The Dplyr section taught by Professor Roger Peng was the best explained.

2. Links s don't work.

3. The questions are not answered by the teachers.

par Juha R

18 mai 2018

I like the specialization quite a bit as it contains real world data and difficult enough exercises. This particular course is maybe not as good as the other courses I have taken (1,2,5) as the instructions lack a bit of clarity sometimes. However, the peer reviewed assignments are quite tricky and an excellent opportunity for learning. Took my some serious work to get this course done.

par Abdul S

2 avr. 2020

The first thing about the course is that the learning objective was clearer. And the content tied back to it, while also leaving room for self research and study. The project instructions could be a bit clearer, but perhaps the availability of the discussion forum allows this to foster curiosity and community interaction. Overall, it was a worthwhile course.

par Lalit O

17 janv. 2018

All Coursera data science courses have been designed very carefully. I found this course very beneficial as it explains the concepts and also tests the knowledge of the learner through tests.

In this course I learnt basics of fetching data from different sources like, API, Text-file, web-page e.t.c. Also I learnt cleaning data using various techniques.

par Sam M

3 juin 2018

Excellent course! Very useful videos, quizzes, and assignments. Provided the hands-on experience I was looking for. Improvement needs to be done to provide more technical information for doing the quizzes and assignments. Many critical details are being left out and students end up spending way too much time in digging them up via Forum, Google, etc.

par Dev P

2 déc. 2019

Good introduction to getting and cleaning data and very useful learning about the principles of tidy data.

Jeff Leek isn't as good a tutor as Roger Peng and it was a bit frustrating following along at times as no hyperlinks are available for the data. The lessons are just recycled content from Jeff's lectures.

The course project was a good challenge!

par Adetunji O

5 mai 2017

Really great course material. I spent way too much time on the exams and projects, because i believe not enough information was given (had to spend a lot of time searching through discussion forums, stackoverflow, help files etc...and while that is useful experience, it was a lot more time commitment than expected from course description)

par chayan s

25 avr. 2016

Honestly, I wanted to give complete 5 rating to this course, because the content of the lecture is well explained. But one feature I didn't like at all and that is Coursera has made it mandatory for the users to purchase the course in order to submit the quiz/assignment which I personally didn't like it. Except that the course is awesome.

par Dylan B

11 déc. 2017

Good course, better structured than course 1 and 2 of this programme. However, still a few of frustrating moments when the lecturers all of a sudden use language/jargon that cannot be understood by a beginner with little background in computer science (like me). Final coursework is ambitious, but answers can be found on the internet.

par Deleted A

25 janv. 2016

The course is more challenging than the prior two courses, but also very rewarding. I can apply the skills from this course directly to my work, and produce results.

A bit drawback is the some quiz questions and the final assignment can use more detailed instructions. Providing the clarity doesn't necessarily gives away the answers.

par Lou O

8 août 2016

It's pretty good. It should provide a high-level approach to "getting and cleaning data"....and how it fits into the high-level roadmap of what Data Scientists do. Some of the quiz questions were written poorly - I expect better from an online course from a prestigious institution. I may have caught a few words misspelled as well.

par Geetha G

13 avr. 2020

The assignments were tough for me to handle. There should have been a step by step guide for the programs to be written just as in SWIRL exercises. Otherwise, the lectures are well understood. In general, I am quite fascinated by this course and look forward to learning more and better from other sources as well.

par Abhinay R

28 juin 2016

Very useful concepts taught in this course, one would be crawling data consistently as a full time data scientist. But even thought the pacing and project were good, I found the videos a touch boring. Nevertheless, it is part of the whole specialization, which in itself is serious education :)

par Oleg S

24 avr. 2016

Good course. I like it. However, it looks a lack of explanations or training for me. It possible, there too much material for this number of lectures, or just I haven't due background. Maybe, it makes sense to add more swirl courses for people like me to gain a proper comprehension.

par Marta R

12 juin 2019

I think the course in general is really good. The videos are very useful and although the subjects are not that intuitive, I find the materials very clear. The only negative point I can find is the fact that the quizzes are much harder than the final project and a bit to complicated!

par Ted L

27 mars 2017

The course of getting data is a little difficult, however, the cleaning data course is excellent. Using the package of "dplyr", I learn how to clean data effectively. My suggestion is that getting data from website can teach less, and the cleaning data course can add more practices.

par Kyle H

28 déc. 2017

A nice course overall, perhaps a few more excercises on the cleaning data side would have been helpful. In particular the melt, dcast and tidyR functions are tough to understand when seen for the first time. I did do the swirl activities for these and that helped some.

par Alex H

21 nov. 2018

The course has very valuable information and teaches many useful skills. I would absolutely recommend it to anyone with an interest in programmatic data analysis and/or data science. It's not a flashy course, but it teaches very necessary support skills.

par Marek T

28 mai 2017

The material seems to be a bit outdated: some websites used in the web scrapping example, JSON APIs etc. seem to have changed they structure so the examples don't really work anymore. Also it's really annoying to have to type out all the URLs by hand.

par Don M

27 mars 2018

Good course, although I felt that the outcome of the project should have been better defined. A mockup of the final results would have save me from wasting time through a misunderstanding of what was required (there is more than one interpretation).

par Karanpreet B

2 mars 2016

Easy to follow. It would be beneficial to recommend this course before or with Introduction to R. Most courses that start teaching R programming, start with teaching about cleaning data before detailing other functionality. Nonetheless, good course.

par Marc E S

24 févr. 2016

Easy to follow. Might be too easy for some people with experience in data analysis. However, the instructors also talk about some frameworks and insights from their experience which could be helpful even for those who have some prior experience.

par Chao L

5 mars 2016

This course itself is quite nice and important.

However, I think that the instructor should have set more assignments to lead us know those techniques better.

Moreover, the ppt can be more detail-oriented.

Overall good but need improvement.

par Fielding I

13 févr. 2021

Some of the assignments reach a bit beyond the scope of the material presented, but by the end of the course you are able to do the final assignments from the material learned. Personally I like Roger Peng's courses in this series more.