May 03, 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.
Oct 26, 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.
교육 기관: Carlos M•
Oct 19, 2017
This course is fantastic! Through it was possible concretely to apply the concepts of BigData through the tool proposed for the course. Due to various difficulties I had to leave. But I'm coming back with all my might. Congratulations to all teachers who make no effort to pass on knowledge in a substantial and substantial way.
교육 기관: Rodney A J•
Jun 06, 2017
This is a terrific course on obtaining data from various sources and then cleaning the raw data obtained to form useful tidy data sets. The course material learned is reinforced using a very interesting peer-reviewed project based on accelerometer and gyroscopic data from collected from typical human activity.
교육 기관: Murat Z•
Feb 11, 2018
Great course for data mining and cleaning. If you planning to take Reproducible Research course, I'd recommend to at least audit that course's second week for markdown and knitr skills prior to taking Getting and Cleaning Data course, coz you're going to face need for those skills during the course project.
교육 기관: Sachi B•
Feb 20, 2018
Good intro to several commands needed for cleaning and preparing data. Final assignment was challenging enough that made me dig deeper into commands. Since there are several ways of accomplishing the same task in R, grading the other students helped see what others have done - some of them were slick!
교육 기관: Aki T•
Oct 24, 2019
This course was excellent and fundamental in order to even start a data analysis. It sets the foundation for how to read and treat the data, which is as the instructor mentioned, often overlooked. Thank you very much for taking the time to break the cleaning process into each comprehensive pieces.
교육 기관: Nino P•
May 24, 2019
A bit tough course with topics of getting the data since I don't know much about file types, but cleaning part is a must do for every data scientist. dplyr and tidyverse is the base of R and nowadays I only use dplyr for my data wrangling. Highly recommendable course and specialization.
교육 기관: Sudheergouda P•
Dec 31, 2018
The course project was really helpfull in understanding how the data is presented to datascientists. Now to get the jist of the data we have to go through assembling, cleaning and cutting the data.. It was a challenged to understand the data.. assembling the data was a lot of fun in R..
교육 기관: Fernando V•
Dec 14, 2016
A great course. I mean, It has not been easy, I have spent a lot of time in front of the PC practising and doing exercises, but this time and the tools that I have learned make me much more agile and confortable with R, and I have seen the big possibilities that this language has.
교육 기관: Christopher L•
Jul 18, 2017
great course, I am fairly familiar with R in my line of work but this was a great opportunity to practice web-scraping. I might even switch from a dplyr-centric wrangling workflow to one centered on data.table in my personal and professional work. more compact and faster!
교육 기관: Carlos M•
Dec 22, 2016
Difficult but valuable. You will be watching the videos repeatedly and become a regular at StockOverflow but it was completely worth it. Getting, cleaning, and processing data is pretty much 80%+ of the job, this course's information is vital to any future data worker.
교육 기관: Gilvan S•
Feb 11, 2017
Excellent course. It gets through the "dirty job" of obtaining data from diverse sources (including API, web, and others), cleaning it, and transforming it into a "tidy" dataset. Highly recommended, along with the R programming course (which you should take first).
교육 기관: Scott C•
Feb 17, 2018
Good overview of what it means to get and clean your own data. Really enjoyed the final project as it challenged you to, with minimal guidance, think through what a tidy dataset really means, and figure out how to make that happen with the dataset you are provided.
교육 기관: Tim S•
Mar 24, 2016
For someone with no programming background and limited experience working with data, this was a challenging, sometimes frustrating, course. But perseverance through the struggle can end in a deep sense of satisfaction. Happily, this is how it was - quite rewarding.
교육 기관: Gbolahan•
Sep 07, 2016
Wonderful course. gets you through the basics and beyond in getting and cleaning data from diverse sources. Very well thought and explained. There is a lot to be learnt from this course, and it requires devoting a good amount of time to let the material sink in.
교육 기관: Diego A S R•
Jul 04, 2020
Good course, but needs an update. Week 2 was really difficult compared to what was explained in the lectures and regex expressions should be explained using R, it was a little hard to learn to use them directly in R. I feel that I learned a lot in this course.
교육 기관: Randal N•
Jan 23, 2018
Very enlightening course. It is the first course where I felt like I was actually doing something data sciency. Would recommend even as a stand alone course because I have now come to appreciate the importance of tidy data in performing successful analyses.
교육 기관: Keat C C•
Nov 07, 2016
Really can learn practical skills! I like that each sub course of data science specialisation just focus on a certain areas and takes only 4 weeks, this way I won't be overburden between work and learning, and also easier for me to absorb the new skills.
교육 기관: Waleed A•
Jan 31, 2018
Another brilliant course from Johns Hopkins University in the data science specialisation. Data preparation is a step where an analyst may spend considerable time before beginning any analysis task. I found this course useful and practical. It provided
교육 기관: Daniel M D V•
Sep 03, 2019
Excellent! From my point of view, this is the best course so far. The general concepts that are thought here can be applied to any programming language you use for data analysis. The specific R concepts really shows the power R has to manipulate data.
교육 기관: Kunal P•
Dec 15, 2019
This was one of the best class. Recommend more side reading material on data. SWIRL has a reading link but the link is not provided anywhere else on the board. Also, it would be beneficial if the links can be made clickable in lecture slides. Thanks.
교육 기관: Martin H•
Aug 14, 2016
Exellent course, which brings you to the next level of a Data Scientist.
Getting and Cleaning data principles can be used in alot of situations. I found the build up of this and the assignment at the end to be very well tought trough and important.
교육 기관: Oleksandr K•
Apr 15, 2018
Very good course and lectures. However, it would be good to have a book covering all of the material in this course. That would make work on final project much easier. In my opinion, it is impossible to finish final project in just 2 hours.
교육 기관: Kristin K•
Aug 04, 2017
This course solidified any gaps that were left from the R Programming Course and opens the world of data science to everyone in a very practical way. I really enjoyed the presentation of the material and am very happy I took the class.
교육 기관: Kang I B•
Jun 08, 2017
This was so hard to me, because I didn't know anything about 'Making tidy dataset'. So, when I took a course project, I was struggling to find 'what should I do'. Comprehending raw data is so hard then you think, newbies! Be careful!
교육 기관: Jan K•
Mar 07, 2017
Covers a wide range of topics without loosing transparency. In my opinion requires more work than the other courses, but is really worth a go. You end up having a firm basis for working with data and learning more about the process.