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Learner Reviews & Feedback for Getting and Cleaning Data by Johns Hopkins University

4.5
stars
8,047 ratings

About the Course

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 reviews

HS

May 2, 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

Oct 25, 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 of 1,306 Reviews for Getting and Cleaning Data

By Deleted A

Jan 25, 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.

By Lou O

Aug 8, 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.

By Geetha G

Apr 13, 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.

By Abhinay R

Jun 28, 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 :)

By Oleg S

Apr 24, 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.

By Marta R

Jun 12, 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!

By Ted L

Mar 27, 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.

By Kyle H

Dec 28, 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.

By Alex H

Nov 21, 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.

By Marek T

May 28, 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.

By Don M

Mar 27, 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).

By Karanpreet B

Mar 2, 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.

By Marc S

Feb 24, 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.

By Chao L

Mar 5, 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.

By Fielding I

Feb 13, 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.

By Ashish T

May 5, 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.

By Romit

Oct 4, 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.

By Owen P

Dec 19, 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!

By Gabriel T d O

Mar 17, 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.

By pascal b

Feb 21, 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

By Luis G N C

May 1, 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.

By Lorenzo R

Jul 7, 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.

By Timofan M

Aug 29, 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.

By Valerie H

Nov 24, 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.

By Jesus M S

Apr 22, 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.