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 HopkinsAcerca de este Curso
170,489 vistas recientes
Resultados profesionales del estudiante
37%
comenzó una nueva carrera después de completar estos cursos
37%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
13%
consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
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. 20 horas para completar
Inglés (English)
Subtítulos: Francés (French), Chino (simplificado), Vietnamita, Coreano, Ruso (Russian), Inglés (English)
Qué aprenderás
Understand common data storage systems
Apply data cleaning basics to make data "tidy"
Use R for text and date manipulation
Obtain usable data from the web, APIs, and databases
Habilidades que obtendrás
Data ManipulationRegular Expression (REGEX)R ProgrammingData Cleansing
Resultados profesionales del estudiante
37%
comenzó una nueva carrera después de completar estos cursos
37%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
13%
consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
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. 20 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 ejercicio de práctica
Week 1 Quiz30m
1 hora 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 hora para completar
5 videos (Total 41 minutos)
5 videos
Reading from HDF56m
Reading from The Web6m
Reading From APIs7m
Reading From Other Sources4m
1 ejercicio de práctica
Week 2 Quiz30m
11 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.
11 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 lectura
Practical R Exercises in swirl Part 210m
1 ejercicio de práctica
Week 3 Quiz30m
5 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.
5 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 ejercicio de práctica
Week 4 Quiz30m
Reseñas
Principales reseñas sobre GETTING AND CLEANING DATA
por HS2 de may. 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.
por BE25 de oct. 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 CW6 de ago. de 2020
I think that the level of difficulty of the exercises and final assignment does not match with the depth of the lectures; without a textbook, I feel lost, don't have a reference, and have to guess.
por DH1 de feb. de 2016
Easy, mostly instructive Course. The Assignments and quizzes are quite good, and illustrates the lessons very well. See the videos for general presentation, but use the energy on the excersizes.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
¿Qué recibiré si me suscribo a este Programa especializado?
Is financial aid available?
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¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.
