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.
Feb 02, 2016
Easy, mostly instructive Course. The Assignments and quizzes are quite good, and illustrates the lessons very well.\n\nSee the videos for general presentation, but use the energy on the excersizes.
von Joe D•
Apr 15, 2019
Forums! Use the forums. Read them before you start the week's lectures because they often include pinned topics that correct minor errors like broken links and outdated commands, as well as interesting and thoughtful supplementary material. Overall this was a very enjoyable course, Dr. Leek's lectures are straightforward and full of useful examples. I learned about just some of the power of "The Tidyverse" through this course and I'm very grateful for that.
von Chetan T•
Oct 19, 2018
The journey through the entire course was quite exceptional for me. It was great to hone the skills of programming and especially in this digital world where data is key for every analysis, inference, prediction and what not! When everyone looks at neat and tidy data that one can rely on, it is extremely important to understand and know the finer nuances of what it takes to get a nice and efficient dataset and that is the essence of this course.
von Whitchurch S R M•
Jan 29, 2020
This was an awesome course.
I really liked the final project.
Especially creating a Codebook as well as tidying up the data.
I feel I went too much in-depth into creating the codebook as well as the readme file. But in hindsight it was totally worth it.
My advice to future learners. push yourselves to the limit when doing the final project. You will definitely learn much much more by putting in 110% into these hard projects.
von Alexis C•
Aug 11, 2017
Did not like this class when I was taking it, but now (just completed course 7) I realize how very important this class is. "Messy data" use to sound like a buzz phrase to me that people used when they could not generate valuable insights from data made available. Now I realize that that the base R functions and packages highlighted in this class are extremely useful when you need to clean up data in a reproducible way.
von Jose A R N•
Oct 20, 2016
My name is Jose Antonio from Brazil. I am looking for a new Data Scientist career.
Please, take a look at my LinkedIn profile: https://www.linkedin.com/in/joseantonio11
I did this course to get new knowledge about Data Science and better understand the technology and your practical applications.
The course was excellent and the classes well taught by teachers.
Congratulations to Coursera team and Instructors.
von Yusuf E•
Dec 14, 2017
The level of difficulty of this course is on par with R Programming. For the first time in the specialization you will find yourself scouring the forum for tips and suggestions on how to proceed when you get stuck in the quizzes. Fortunately, the mentors are really helpful when it comes to answering questions or clearing obscurities. I really liked this course, in fact much more than R Programming.
von Antonios D•
Nov 14, 2016
This course it's a great job! There is too much information in here and a great amount of knowledge. I would like to say that in my point of view the current lesson should be updated in more different data sets examples that gives the students the opportunity of learning different kind of ways to manypulate some data. There are some standard ways so it would be great if you expand this.
von Chris B•
Nov 22, 2016
It is sometimes daunting and difficult, but now I do understand so much more about downloading files from remote sites and getting them ready for analysis. What I should have done is look to the final project so as get a better understanding of what the project entailed. I also should have done more work replicating the code used in the lessons so as to appreciate how it worked.
von Debayan D•
Jul 25, 2017
The Course Project was daunting at first, but I reviewed my notes over and over again, tried reading from the site where the raw data was made available and constructed images of how the TIDY data should look like. This is a very important course in this specialization. The course has given me an abstract sense of what to expect and what to do while cleaning data.
von Li G•
Jan 12, 2017
Very helpful and pragmatic.
This course gives a general idea on how to get and clean data in r, and specifically taught me how to use "dplyr" and "tidyr".
The assignment is very helpful, too. It forced me to use the knowledge I learned in this course, might be a little bit of hard for a beginner though. Nevertheless, you can still achieve a 100% score!
von Tai C M•
Sep 16, 2017
I am very happy to go through this subject not because of the certification but I learned the steps to import and clean the data. Although this subject is no rocket science, a lot of the data available on the web will require the knowledge that I learned in this subject to enhance the integrity of the data that anyone can download from the web.
von Anthony S•
Nov 03, 2016
Learned a lot! I have now dedicated more time to becoming a data analyst, and eventually a data scientist. The materials used in the videos were helpful and current (for me at least, 30 years young). I have started doing more learning on the kaggle platform as well as doing some hands-on Hadoop related training. Thanks to the professors!
von Carlos A M S•
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.
von 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.
von 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.
von 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!
von 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.
von 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.
von 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..
von 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.
von 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!
von 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.
von 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).
von 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.
von 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.