2 мая 2020 г.
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.
1 февр. 2016 г.
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.
автор: Eduardo R R S•
9 апр. 2021 г.
es muy buen curso recomendada al 100% la ruta solo que siento que deberían hacer una introducción, a purr ya que los bucles de este paquete de tidyverse son mas efectivos que algunas de las funciones que enzeñan.
автор: Angie M•
19 июля 2020 г.
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.
автор: Francisco M M•
20 окт. 2017 г.
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.
автор: Nicholas A•
3 окт. 2017 г.
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.
автор: Herson P C d M•
6 дек. 2016 г.
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!
автор: RONAL O R G•
24 сент. 2020 г.
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.
автор: Nima A•
8 июня 2020 г.
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.
автор: 현 허•
3 мар. 2018 г.
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 Some of courses before were outdated because there are lots of changes in packages or others.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.
автор: Vyasraj V•
26 нояб. 2017 г.
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. ;)
автор: Anna M D C•
2 янв. 2019 г.
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.
автор: Edwin R V C•
7 мар. 2016 г.
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.
автор: Vincent B•
5 нояб. 2017 г.
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".
автор: Gianmarco P•
3 мая 2020 г.
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.
автор: Balaji P•
4 февр. 2018 г.
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
автор: B S•
14 нояб. 2017 г.
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.
автор: BOUZENNOUNE Z E•
3 мар. 2018 г.
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.
автор: Andrew B•
16 окт. 2017 г.
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.
автор: Kelly S•
22 мая 2019 г.
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.
автор: Sudhin B•
17 мар. 2018 г.
So knowledgeable and interesting course. I have learned much about data cleaning and getting from different sources. Finally thanks to coursera team for giving us the opportunity.
автор: Charles K•
6 февр. 2016 г.
This is a very well put together course. It teaches the basics of data cleansing and how to setup data for modeling--by far the most foundational technical aspect of data analysis.
автор: John B•
22 сент. 2018 г.
How to get a clean the data is a very important knowledge for the future data scientist and data analyst. For me this course was very important I very recommend take this course.
автор: Eugene K•
7 янв. 2018 г.
Great course on tidy data. Very useful in understanding how to use different types of data (csv, XML, API) and how to manipulate the data so that you can perform analyses on it.
автор: Mohammad A•
16 июня 2018 г.
Excellent course, and quizzes and lecture were very teaching. But some materials needs to be updated up to date , like subsetting columns in data.table the slides were absolute.
автор: João F•
17 окт. 2017 г.
Great ready-to-use skills for common tasks of a Data Scientist. Lays the foundations for further self-development in the topics taught. Heavy on R. Very challenging assignments.
автор: Amsalu B B•
23 мая 2020 г.
This specific course is good but when it comes to the assignments, it's more confused than the course work and the description of the assignment is unclear too, at least to me.