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Bewertung und Feedback des Lernenden für Getting and Cleaning Data von Johns Hopkins University

4.5
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7,994 Bewertungen

Über den Kurs

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....

Top-Bewertungen

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. Okt. 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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851 - 875 von 1,295 Bewertungen für Getting and Cleaning Data

von Marta R

12. Juni 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!

von Ted L

27. März 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.

von Kyle H

28. Dez. 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.

von 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.

von 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.

von Don M

27. März 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).

von Karanpreet B

2. März 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.

von Marc E S

24. Feb. 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.

von Chao L

5. März 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.

von Fielding I

13. Feb. 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.

von Ashish T

5. Mai 2018

Good way to get introduced to the tiny verse packages and importing, prepping datasets before they can used for exploratory analysis and modelling.

Could have gone a bit more in depth on how to deal with dates, and regular expressions.

von Romit

4. Okt. 2016

Course is great, specially the assignments. Don't depend on lecture videos too much, this is a programming course so you'll have to get your hands dirty. Don't forget to work on swirl() package, its a great way to learn interactively.

von Owen P

19. Dez. 2016

The content is good for the most part. There are some errors in the instructions to the assignment which make the assignment more like a real-world spec than the authors probably intended, but that's not necessarily a bad thing!

von Gabriel T d O

17. März 2017

Great course. Could be more interactive and could have more detailed instructions for the Course Project. Last task for the Course Project uses a function that is not covered in previous lessons, which I think is not OK.

von pascal b

21. Feb. 2017

I really started to get interested in R only when I started this course.

Before that, it was just an old, cryptic language that could not do more than what I can do with Excel.

Now I am starting to see the full potential

von Luis G N C

1. Mai 2019

It is a good course. I believe that the final project is challenging but quite extensive and requires dedication to solve it. I would have liked for this course, to establish a formal methodology for data cleansing.

von Lorenzo R

7. Juli 2019

Some files that were used for the examples were no longer accessible. Updates to the xlsx package also were not reflected or discussed. As I noticed on the forums several students had issues with java dependencies.

von Timofan M

29. Aug. 2019

The 3rd course in the specialization was great in terms of the materials presented.

But the "homework" requirements were a little bit unclear most of the times, even though the actual solution was fairly simple.

von Valerie H

24. Nov. 2016

Capstone project is a little ambiguous. Although that's good experience having to find a way to reason out what the objective is based on limited information.

Introduction to chained dplyr is incredibly useful.

von Jesus M S

22. Apr. 2020

Clearly structured course, but as with previous courses of the Data Science program, there is a gap regarding coding skills which the course does not till for those of us lacking a programming background.

von Juan P L R

10. Aug. 2020

Most of the course was interesting, well-designed and useful. Some lectures and links have to be upgraded. This is a really good course if you want to know what possibilities you have to get data with R.

von Sean F

1. Nov. 2018

Good course, instructors are very knowledgeable. Would be good to add more practical lessons and extend the course. As they say, repetition is the law of learning. Thank you for helping me get this far!

von Tony W

5. Mai 2016

The assignment was excellent but challenging, instruction wasn't too clear or obvious though, struggled for a while (good kind of struggle)

The lecture was okay but the Swirl part is always fantastic.

von Carlos G W

7. Aug. 2020

I think that the level of difficulty of the exercises and final assignment does not match with the depth of the lectures; without a textbook, I feel lost, don't have a reference, and have to guess.

von NEVIN T K

19. Mai 2020

The 'cleaning data' part was explained pretty well... I do feel he could've gone into more detail for the 'gathering data' part- especially the webscraping part. Other than that, great course!