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

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7,870 Bewertungen
1,290 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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1076 - 1100 von 1,253 Bewertungen für Getting and Cleaning Data

von Daniel P

24. Okt. 2019

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good. I like the videos and the assignment. There is cerain redundancy of information. Much of the "new" information was already elaborated in the previous courses of the same specialization. Additionally, the grading system is based on other students whose knolledge may be not beyond the course scope and submitting an inovative solution can mean not passing the course.

von Edward C

15. Feb. 2017

Lectures add very little to what you get simply by looking at the slides on your own. Facilitators are expert biostatisticians, not R programmers, and sometimes their explanations of R functionality is superficial and imprecise. The assignments are rigorous and challenging, however, and if you take the time to go through all of the exercises you will gain valuable knowledge.

von Youssuf A

22. Apr. 2020

The theory is explained well and there is not much of a problem to follow the content. But there is a huge gap between understanding the theory and applying it practically. After one finished all lessons one is just not well enough prepared to solve the assignments. The problems, which one faces, are far too difficult to address without previous knowledge / experience.

von Alexis C

12. Okt. 2018

first two week need an update, because many thing on the videos dint work easy on the computer, is not bad to look for more information about the subject on the web, but at least made that the examples on the videos work fine went anybody run the scripts on theirs computers, last two week are good a brief summary of R, and how to work with data, love those 2 weeks

von Andrew M T

25. Okt. 2017

The course fits nicely in the specialisation, and I enjoyed the Swirl exercises, which are massively useful. The structure, though, is a bit chaotic, with loads of topics touched only briefly. Perhaps less is good here. Also, I found that the Swirl exercises were repeated across Weeks, and sometimes they didn't have codes to earn extra credits.

von chris

31. Mai 2016

Peer reviewed assessment with students who are unsure of the correct answers = unsure if solution is correct. Perhaps a formal process (same as previous course where a SHA commit is submitted and source is automatically downloaded (and plagiarism detected) & run to verify the output that columns / data meet an acceptable criteria

von Tareq R

22. Okt. 2018

I think some concepts could have been taught better with simple examples first, and then gradually move to more complex ones, but using noisy data blur the learning objective , and again... the instructors are just showing up a slide.. I think the power of video and illustrations could have been better utilized

von Allyson D d L

5. Nov. 2021

The course is good to learn more R commands but only in the last week there is a practical assignment. I think if all weeks could have practical assignments this course would be excellent. In this assignment we don't use all the commands that we learnt. So, this course has a lot to improve.

von Debjit C

6. Juli 2020

I had a very interesting experience in the course. Thanks to all the help from the discussion forum and data science communities such as StackOverflow . They have the best resources to learn.

The assignments were a bit difficult to understand but once understood, it was quiet easy to solve.

von Bruno V

22. Juni 2020

The course is good but should update its links and go deep into the regex syntax. Moreover, the tasks of the assignment was not difficult. However, it was not easy to understand the tasks as they were not well explained/written. Overall the course is good and I recommend it.

von Ryan B

20. Apr. 2020

Learned some very useful skills, but I found that some of the weeks moved too quickly without sufficiently explaining the background information required (as someone without a data science background) with abstract concepts that were not grounded in application.

von FARROUK_ABDERRAHIM B

12. Okt. 2020

the assignment project was hard and really not enough instruction was given and it was a machine learning data set which made it very hard :) i mean we hadnt seen anythin similar to that during courses :) fix that and change project assignment for final week

von Mark P

12. Juli 2021

T​he course give very broad overviews in the lectures, then drops very difficult questions in the quiz and assiagnments. It is good to push a little and make you dig for solutions on the internet, but the jump in difficulty is too far to make it worthwhile.

von Carlos M C D

8. Feb. 2016

The course is good, but it doesn't really offer all the tools required to pass the exams. I had to take extra courses in other place in order to pass. In addition, the exams some times become a bit too subjective of what the classmates want to grade you.

von Bangda S

10. Nov. 2016

This course provides a lot of methods and strategies about reading data, manipulating data. But I think some important issues in the real world are not discussed enough here, like how to treat missing values, how to deal with messy format data.

von Efe Y

20. Jan. 2021

Had a lot of trouble accessing and downloading datasets from the internet despite I were using the same source codes. Beside teaching how to download data from internet, it would be great if datasets were also included in the course content.

von Dominic H

27. Mai 2018

You will learn valuable tools, techniques and concepts but be prepared to feel overwhelmed (if you have no computer science background whatsoever) by quizzes and the assignment which require you to do research stuff outside of this course.

von sunsik k

18. Juli 2017

Quite disappointed at 'Getting data' part because of lack of explanation(I only had to learn extra sources to understand) but satisfied with 'Cleaning data' part. It would have been more useful if course described how to use GitHub, at the

von Fabiana G

23. Juni 2016

The content of the course is good, but it seems abandoned - some links are outdated or don't work. I think it would be a much better experience for students if these first courses in the specialization got more love from the instructors.

von Steve W

3. Feb. 2016

The lecture material was high level, and didn't seem to be a good preparation for the quizzes.

The description for the final project was not very detailed, and the grading rubric likewise was not very specific for peer review.

von Andrew G

28. Juli 2018

I thought the course project grading was supposed to focus on what we learned in class, not almost entirely on creating readme and codebook files. Also, the explanation of what was expected for the project was NOT CLEAR,

von Wentao B

2. Apr. 2016

The content of the course is too general, with too brief introduction of some commands in the lecture notes(slides), I don't think it would be very helpful for the students to deal with some real complicated problems.

von Justin z

13. Apr. 2017

brought up some good concept inside, like "tidy data", but not in detail, how to grab data from different source shouldn't be difficult. should have more focus on talking about data.table, "tidy data" principles etc.

von Bekhzod A

13. März 2016

Hi all,

Course provides interesting insight to getting and cleaning data. However, the course misses practical examples (not only showing the code in the slides, but also presenting how it works in R or RStudio).

von Ehab H A

4. Feb. 2019

This course was too hard for me compared to the first two in the program. Not sure whether it is because of my limited background in the subject area, or because of the abrupt shift in level from course 2 to 3.