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: Tomer E•
Jun 21, 2020
Very nice course.
helped to understand how to find sources of data (I found that extremely important), and strengthened my R skills.
It would be nice though to have the links which were shown in the slides available for the students.
교육 기관: Miguel C•
Dec 20, 2017
This is a very complete course. It covers the basics of what you have to know to adquire data from different sources and filter that data to be used in further steps of data analysis. It offered great notions on Data Mining also.
교육 기관: Tim S•
Sep 17, 2017
I learned a lot. The videos were clear and helpful. The assignments were just the right level, not too easy and not hard but still challenging.
The swirl package for interactive practice/learning is also very helpful. I Love it!
교육 기관: Dmytro D•
Mar 15, 2016
I am happy now with the single file HTML Documentation for the whole course, generated from md-Files in the cloned repo
It is much handier than the standard downloadable PDFs.
교육 기관: Dominic C•
Aug 01, 2016
Using R with training through your course seemed almost too easy, your book also greatly helped, thank you for such a well designed course which is so practically based and geared towards commercial programmers like myself.
교육 기관: Орехов А И•
Mar 12, 2020
This course is very interesting and not as difficult as it seems. I learned many new stuff about data analysis in R, as well as how to work in swirl, something I have never encountered before. Otherwise, awesome course! :)
교육 기관: Vinayak•
Jul 26, 2019
Great content, challenging assignments and quality videos. Loved the coursework and grateful to have learned from such highly experienced professors. Thanks Coursera and Johns Hopkins University for making this happen!
교육 기관: Abhiram R P•
May 17, 2017
Good course design, challenging material. I love the fact that the course doesn't spoon feed everything, we are encouraged to learn more on our own. This course gives you almost everything required to handle data in R.
교육 기관: Angie M•
Jul 19, 2020
One of the most useful courses I've taken so far in Coursera from a beginners perspective. The course does need some updating but overall I was able to complete the assignments with the information provided.
교육 기관: Francisco M M•
Oct 20, 2017
Me pareció un excelente curso, muy didáctico y con mucha información adicional para poder estudiar por nuestra cuenta para lograr una mayor profundidad en algunos temas en especial. Lo recomendaría sin duda.
교육 기관: Nicholas A•
Oct 03, 2017
I really enjoyed this class. Cleaning data is not very difficult, but it is a very important aspect of Data Science. This class taught me the importance on making data easily readable on top of the process.
교육 기관: Herson P C d M•
Dec 07, 2016
Excepcional, estes cursos estão abrindo completamente minha mente para novos horizontes, novas possibilidades. Enfim, estou cada dia mais motivado e mais entusiasmado com tudo de novo que tenho aprendido!
교육 기관: Ronal O R•
Sep 25, 2020
It´s a good course to learn how to sort and get a tidy data, the course project it´s a good challenge but it took time to get the 4 perviews, I think many people have problems with the Git Hub account.
교육 기관: Nima A•
Jun 08, 2020
A very useful course. The audio quality of some lectures (especially those by the main instructor) was not good. This course completes the sister course of R programming and they work together.
교육 기관: 현 허•
Mar 03, 2018
I really really loved this course. Some of courses before were outdated because there are lots of changes in packages or others. However, materials in this course were not changed that much.
교육 기관: Vyasraj V•
Nov 26, 2017
A lot of insight and practical knowledge of cleaning data that is available in many places in the Internet. I loved this course and it took me 2 tries to pass the peer graded assignment. ;)
교육 기관: Anna M D C•
Jan 02, 2019
It was pretty hard for someone like me who has a weakness in programming but it provided sufficient exposure and tasks for me to learn within my capabilities. I did enjoy its challenges.
교육 기관: Edwin R V C•
Mar 07, 2016
Excellent course. It helps to complement the knowledge of data analysis. The project was quite interesting and illustrative, especially considering that they were real experimental data.
교육 기관: Vincent B•
Nov 05, 2017
Very good course! It is a topic which is very often underestimated and we all need to learn to get more productive on this, as most of the time is spend on it in the "real world".
교육 기관: Gianmarco P•
May 03, 2020
Very well done. Clear example and balanced explanation. Big advantage if you spend more time looking at the suggested readings. I found usefullpeer- review thanks to other students.
교육 기관: Balaji P•
Feb 04, 2018
The course is an excellent introduction to the dplyr package and string manipulation in r. I thought the assignment at the end of the course was a little vague and hard to understand
교육 기관: B S•
Nov 14, 2017
Great course if you are working with R. I learned how to load data in R and various handy features (plyr, dplyr, lubridate packages) to clean data before starting the data analysis.
교육 기관: BOUZENNOUNE Z E•
Mar 03, 2018
Amazing, you get to see almost every aspect of data science.
It is true that you won't get deeepeeeer, but this course allow you to not fear any kind of data science. That's amazing.
교육 기관: Andrew B•
Oct 16, 2017
This course is very enlightening. The techniques demonstrated in this course are critical for gathering raw data from various sources and turning it into useful data for analysis.
교육 기관: Kelly S•
May 22, 2019
I really liked this course and believe that my work, although seemingly noob-ish, will get much better as I see others works from the peer review and examples noted in the lessons.