In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
ofrecido por
Universidad Johns HopkinsAcerca de este Curso
801,612 vistas recientes
Resultados profesionales del estudiante
34%
comenzó una nueva carrera después de completar estos cursos
32%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
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. 18 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Chino (simplificado), Italiano, Vietnamita, Coreano, Alemán (German), Ruso (Russian), Turco (Turkish), Inglés (English), Español (Spanish)
Qué aprenderás
Set up R, R-Studio, Github and other useful tools
Understand the data, problems, and tools that data analysts use
Explain essential study design concepts
Create a Github repository
Habilidades que obtendrás
Data ScienceGithubR ProgrammingRstudio
Resultados profesionales del estudiante
34%
comenzó una nueva carrera después de completar estos cursos
32%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
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. 18 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Chino (simplificado), Italiano, Vietnamita, Coreano, Alemán (German), Ruso (Russian), Turco (Turkish), Inglés (English), Español (Spanish)
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
5 horas para completar
Data Science Fundamentals
In this module, we'll introduce and define data science and data itself. We'll also go over some of the resources that data scientists use to get help when they're stuck.
5 horas para completar
5 videos (Total 40 minutos), 2 lecturas, 5 cuestionarios
5 videos
What is Data Science?9m
What is Data?6m
Getting Help10m
The Data Science Process9m
2 lecturas
Welcome5m
A Note of Explanation2m
5 ejercicios de práctica
What is Data Science?30m
What is Data?30m
Getting Help Quiz30m
Data Science Process30m
Module One Summative Quiz30m
5 horas para completar
R and RStudio
In this module, we'll help you get up and running with both R and RStudio. Along the way, you'll learn some basics about both and why data scientists use them.
5 horas para completar
5 videos (Total 34 minutos)
6 ejercicios de práctica
Installing R30m
Installing R Studio30m
RStudio Tour30m
R Packages30m
Projects in R30m
Module Two Summative Quiz30m
4 horas para completar
Version Control and GitHub
During this module, you'll learn about version control and why it's so important to data scientists. You'll also learn how to use Git and GitHub to manage version control in data science projects.
4 horas para completar
4 videos (Total 28 minutos)
4 videos
Github and Git8m
Linking Github and R Studio4m
Projects under Version Control4m
5 ejercicios de práctica
Version Control30m
GitHub and Git30m
Linking Git/GitHub and RStudio30m
Projects under Version Control30m
Module Three Summative Quiz30m
5 horas para completar
R Markdown, Scientific Thinking, and Big Data
During this final module, you'll learn to use R Markdown and get an introduction to three concepts that are incredibly important to every successful data scientist: asking good questions, experimental design, and big data.
5 horas para completar
4 videos (Total 34 minutos)
5 ejercicios de práctica
R Markdown30m
Types of Data Science Questions30m
Experimental Design30m
Big Data30m
Module Four Summative Quiz30m
Reseñas
Aspectos destacados
"Foundational tools" en 243 reseñas
"Introductory course" en 1056 reseñas
Principales reseñas sobre THE DATA SCIENTIST’S TOOLBOX
por SR14 de mar. de 2017
It would be better if we can attempt the assignments even if we are not enrolled to the course. It would really help us to evaluate ourselves about the extent to which we have understood the concepts.
por SF14 de abr. de 2020
As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.
por US12 de oct. de 2017
Great course for a beginner. But, since I knew most of the content from previous works, there was not much new learning for me. I am confident the later courses will enhance my knowledge a great deal.
por LR7 de sep. de 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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
¿Qué recibiré si me suscribo a este Programa especializado?
Is financial aid available?
¿Recibiré crédito universitario por completar el Curso?
¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.
