Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data.
ofrecido por
Universidad Johns Hopkins
Acerca de este Curso
138,620 vistas recientes
Resultados profesionales del estudiante
39%
comenzó una nueva carrera después de completar estos cursos
36%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Habilidades que obtendrás
Data ManipulationRegular Expression (REGEX)R ProgrammingData Cleansing
Resultados profesionales del estudiante
39%
comenzó una nueva carrera después de completar estos cursos
36%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Aprox. 15 horas para completar
Inglés (English)
Subtítulos: Francés (French), Chino (simplificado), Vietnamita, Coreano, Ruso (Russian), Inglés (English)
ofrecido por
Universidad Johns Hopkins
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Programa - Qué aprenderás en este curso
2 horas para completar
Week 1
In this first week of the course, we look at finding data and reading different file types.
2 horas para completar
9 videos (Total 67 minutos), 4 lecturas, 1 cuestionario
9 videos
Raw and Processed Data7m
Components of Tidy Data9m
Downloading Files7m
Reading Local Files4m
Reading Excel Files3m
Reading XML12m
Reading JSON5m
The data.table Package11m
4 lecturas
Welcome to Week 110m
Syllabus10m
Pre-Course Survey10m
Practical R Exercises in swirl Part 110m
1 ejercicios de práctica
Week 1 Quiz10m
1 horas para completar
Week 2
Welcome to Week 2 of Getting and Cleaning Data! The primary goal is to introduce you to the most common data storage systems and the appropriate tools to extract data from web or from databases like MySQL.
1 horas para completar
5 videos (Total 41 minutos)
5 videos
Reading from HDF56m
Reading from The Web6m
Reading From APIs7m
Reading From Other Sources4m
1 ejercicios de práctica
Week 2 Quiz10m
10 horas para completar
Week 3
Welcome to Week 3 of Getting and Cleaning Data! This week the lectures will focus on organizing, merging and managing the data you have collected using the lectures from Weeks 1 and 2.
10 horas para completar
7 videos (Total 60 minutos), 1 lectura, 4 cuestionarios
7 videos
Summarizing Data11m
Creating New Variables10m
Reshaping Data9m
Managing Data Frames with dplyr - Introduction3m
Managing Data Frames with dplyr - Basic Tools12m
Merging Data6m
1 lecturas
Practical R Exercises in swirl Part 210m
1 ejercicios de práctica
Week 3 Quiz10m
6 horas para completar
Week 4
Welcome to Week 4 of Getting and Cleaning Data! This week we finish up with lectures on text and date manipulation in R. In this final week we will also focus on peer grading of Course Projects.
6 horas para completar
5 videos (Total 34 minutos), 2 lecturas, 3 cuestionarios
5 videos
Regular Expressions I5m
Regular Expressions II8m
Working with Dates6m
Data Resources3m
2 lecturas
Practical R Exercises in swirl Part 410m
Post-Course Survey10m
1 ejercicios de práctica
Week 4 Quiz10m
Revisiones
Principales revisiones sobre GETTING AND CLEANING DATA
por BEOct 25, 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 DHFeb 1, 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.
por ATNov 19, 2017
Very interesting and enjoyed doing the Assignment.\n\nbut the assignment instructions are not clear.A lot of time was wasted trying to figure out what data is what are what are we interested in.
por ARMay 13, 2018
Loved the structure of the course. Learned a lot. The course project seemed a little funky , especially creating the codebook for an already existing set of data but was a useful teaching aid.
por WCOct 31, 2016
This course is amazing! I have spent the majority of my time in R merely doing analytics. This course taught me the tools needed to go out and grab the data that I need for those analytics.
por VVNov 25, 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. ;)
por ACJan 1, 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.
por JSOct 18, 2016
The course material is ok - it would really need a book like the other courses have. It is much easier to check something from a book than slides/video when doing the assignments etc. .
por BPFeb 3, 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
por RRJul 9, 2017
I found the last project insufficiently explained. I was struggling in understanding what the task is. A bit more clear task description (as in Course 2) would be really appreciated.
por RDNov 9, 2016
Good coverage of topics. A bit scattered in early slides and assignments were often inconsistent with coursework. Overall a great introduction of what to expect when gathering data.
por KSMay 21, 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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
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