2 de mai de 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.
25 de out de 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.
por James L J J•
26 de dez de 2019
The Value of the course is in the course projects. I found that working through them really accelerated the understanding.
por Xun Y•
10 de jul de 2017
Great course, providing very useful information. It might be better to provide few examples for codebook and readme files.
por João A P B•
25 de fev de 2017
Amazing course! Even after a few years using R in a daily basis, I still learned quite a bit of new / useful information.
por David R•
3 de set de 2018
Great course covering a wide range of data types likely to be encountered in the field of data science. Well explained.
por Anne M•
10 de jan de 2016
Really great class. I found the lectures easy to follow. The quizzes and homework helped me master the course material.
por Andrés H V•
28 de jun de 2020
I believe it was a very good course ,challenging and interesting. As a beginner in Data Science and R I learned a lot.
por Cathryn S•
2 de jan de 2017
A good course, which helped me understand how to get data off the web and from other sources, and improved my R skills
por Nelson S S•
10 de nov de 2020
Muchas gracias por compartir sus conocimientos y el gran aporte que hacen en éstas épocas de pandemia
por FARZAD R•
26 de fev de 2017
This course is very interesting, useful and practical
I appreciate for all of efforts of my professors in this course
por Pitchayen S•
14 de fev de 2017
Very fundamental things that all data scientist must learn. You will know how useful of data.table and dplyr package.
por Anastasia T•
19 de out de 2016
Interesting, challenging course. Opened lots of questions to the topic and gave a good direction to find the answers.
por Cristóbal A•
2 de abr de 2016
Entrega conceptos y herramientas útiles. El material es de buena calidad y es presentado de una forma bastante clara.
por Suryadipta D•
28 de mar de 2018
Very simple and introductory course that teaches the concepts really well. Forms a brilliant specialization course.
por Steven C•
15 de mar de 2017
Great coverage of useful R libraries for retrieving and tidying up data, and difficult but valuable course project.
22 de mar de 2016
Very good class for a beginner. Helps become more comfortable with R programming and aspects of getting data into R
por Vivek G•
8 de nov de 2019
Challenging course for working professionals from time perspective but very educative and useful. I learned a lot.
por Vipin J•
20 de nov de 2018
A must take course for data science carrer... Very good concept explaination with really good hands on with Swirl.
por Philip S•
9 de jul de 2018
Excellent survey of data cleaning methods, good grounding in tidyverse tools, builds nicely on previous 2 courses.
por Matheus L N•
6 de jun de 2018
was a hard module for whose isn't a programmer, but was well done structureted to easy learning with hard studying
por ayush j•
18 de abr de 2018
Many tricks and tips tools, many good functions. its really way completing my need on R at initial level i needed.
por Ekta R•
27 de jun de 2017
I am very much enjoyed the course. However, a lot of dedication is required as a beginner to complete this course.
por Aman G•
15 de jun de 2017
Really helped me learn the different sources of acquiring data into R and methods to transform data into tidy data
por Medha B•
22 de set de 2020
Really great course and i feel a necessary one as it connects and covers many points of the previous 2 courses.
8 de set de 2020
the course provide useful functions and methods and tell us why we should use them in a way easy to understand.
por Francisco M•
12 de jul de 2020
A very demanding course. It took me more than a month to end it but It was worth the effort. I learned a lot.