Acerca de este Curso
4.5
17,078 calificaciones
3,507 revisiones
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Horas para completar

Aprox. 8 horas para completar

Sugerido: 1-4 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English), Francés (French), Chino (simplificado), Griego, Italiano, Portugués (de Brasil), Vietnamita, Ruso (Russian), Turco (Turkish), Hebreo, Japonés...

Qué aprenderás

  • Check

    Create a Github repository

  • Check

    Explain essential study design concepts

  • Check

    Set up R, R-Studio, Github and other useful tools

  • Check

    Understand the data, problems, and tools that data analysts work with

Habilidades que obtendrás

Data ScienceGithubR ProgrammingRstudio
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Horas para completar

Aprox. 8 horas para completar

Sugerido: 1-4 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English), Francés (French), Chino (simplificado), Griego, Italiano, Portugués (de Brasil), Vietnamita, Ruso (Russian), Turco (Turkish), Hebreo, Japonés...

Programa - Qué aprenderás en este curso

Semana
1
Horas para completar
2 horas para completar

Week 1

During Week 1, you'll learn about the goals and objectives of the Data Science Specialization and each of its components. You'll also get an overview of the field as well as instructions on how to install R....
Reading
16 videos (Total 51 minutos), 5 readings, 1 quiz
Video16 videos
The Data Scientist's Toolbox5m
Getting Help8m
Finding Answers4m
R Programming Overview2m
Getting Data Overview1m
Exploratory Data Analysis Overview1m
Reproducible Research Overview1m
Statistical Inference Overview1m
Regression Models Overview1m
Practical Machine Learning Overview1m
Building Data Products Overview1m
Installing R on Windows {Roger Peng}3m
Install R on a Mac {Roger Peng}2m
Installing Rstudio {Roger Peng}1m
Installing Outside Software on Mac (OS X Mavericks)1m
Reading5 lecturas
Welcome to the Data Scientist's Toolbox10m
Pre-Course Survey10m
Syllabus10m
Specialization Textbooks10m
The Elements of Data Analytic Style10m
Quiz1 ejercicios de práctica
Week 1 Quiz10m
Semana
2
Horas para completar
1 horas para completar

Week 2: Installing the Toolbox

This is the most lecture-intensive week of the course. The primary goal is to get you set up with R, Rstudio, Github, and the other tools we will use throughout the Data Science Specialization and your ongoing work as a data scientist. ...
Reading
9 videos (Total 51 minutos), 1 quiz
Video9 videos
Command Line Interface16m
Introduction to Git4m
Introduction to Github3m
Creating a Github Repository5m
Basic Git Commands5m
Basic Markdown2m
Installing R Packages5m
Installing Rtools2m
Quiz1 ejercicios de práctica
Week 2 Quiz10m
Semana
3
Horas para completar
1 horas para completar

Week 3: Conceptual Issues

The Week 3 lectures focus on conceptual issues behind study design and turning data into knowledge. If you have trouble or want to explore issues in more depth, please seek out answers on the forums. They are a great resource! If you happen to be a superstar who already gets it, please take the time to help your classmates by answering their questions as well. This is one of the best ways to practice using and explaining your skills to others. These are two of the key characteristics of excellent data scientists. ...
Reading
4 videos (Total 35 minutos), 1 quiz
Video4 videos
What is Data?5m
What About Big Data?4m
Experimental Design15m
Quiz1 ejercicios de práctica
Week 3 Quiz10m
Semana
4
Horas para completar
2 horas para completar

Week 4: Course Project Submission & Evaluation

In Week 4, we'll focus on the Course Project. This is your opportunity to install the tools and set up the accounts that you'll need for the rest of the specialization and for work in data science....
Reading
1 reading, 1 quiz
Reading1 lecturas
Post-Course Survey10m
4.5
3,507 revisionesChevron Right
Dirección de la carrera

36%

comenzó una nueva carrera después de completar estos cursos
Beneficio de la carrera

83%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

Principales revisiones

Aspectos destacados
Introductory course
(1056)
Foundational tools
(243)
por LRSep 8th 2017

It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.

por AMJul 22nd 2017

Great Primer for what Data Science is about. It also provides the infrastructure of tools needed. This was what I was after, a way to provide other data scientist hardware and infrastructure support.

Instructores

Avatar

Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
Avatar

Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
Avatar

Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

Acerca de Johns Hopkins University

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....

Acerca del programa especializado Data Science

Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material....
Data Science

Preguntas Frecuentes

  • 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.

  • 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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