Informações sobre o curso
4.5
16,007 ratings
3,321 reviews
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....
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
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Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
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Sugerido: 1-4 hours/week

Aprox. 8 horas restantes
Comment Dots

English

Legendas: English, French, Chinese (Simplified), Greek, Italian, Portuguese (Brazilian), Vietnamese, Russian, Turkish, Hebrew

O que você vai aprender

  • 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 você terá

Data ScienceGithubR ProgrammingRstudio
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Clock

Sugerido: 1-4 hours/week

Aprox. 8 horas restantes
Comment Dots

English

Legendas: English, French, Chinese (Simplified), Greek, Italian, Portuguese (Brazilian), Vietnamese, Russian, Turkish, Hebrew

Programa - O que você aprenderá com este curso

1

Seção
Clock
2 horas para concluir

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 vídeos (Total de 51 min), 5 leituras, 1 teste
Video16 videos
The Data Scientist's Toolbox5min
Getting Help8min
Finding Answers4min
R Programming Overview2min
Getting Data Overview1min
Exploratory Data Analysis Overview1min
Reproducible Research Overview1min
Statistical Inference Overview1min
Regression Models Overview1min
Practical Machine Learning Overview1min
Building Data Products Overview1min
Installing R on Windows {Roger Peng}3min
Install R on a Mac {Roger Peng}2min
Installing Rstudio {Roger Peng}1min
Installing Outside Software on Mac (OS X Mavericks)1min
Reading5 leituras
Welcome to the Data Scientist's Toolbox10min
Pre-Course Survey10min
Syllabus10min
Specialization Textbooks10min
The Elements of Data Analytic Style10min
Quiz1 exercício prático
Week 1 Quiz10min

2

Seção
Clock
1 hora para concluir

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 vídeos (Total de 51 min), 1 teste
Video9 videos
Command Line Interface16min
Introduction to Git4min
Introduction to Github3min
Creating a Github Repository5min
Basic Git Commands5min
Basic Markdown2min
Installing R Packages5min
Installing Rtools2min
Quiz1 exercício prático
Week 2 Quiz10min

3

Seção
Clock
1 hora para concluir

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 vídeos (Total de 35 min), 1 teste
Video4 videos
What is Data?5min
What About Big Data?4min
Experimental Design15min
Quiz1 exercício prático
Week 3 Quiz10min

4

Seção
Clock
2 horas para concluir

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 leitura, 1 teste
Reading1 leituras
Post-Course Survey10min
4.5
Direction Signs

36%

comecei uma nova carreira após concluir estes cursos
Briefcase

83%

consegui um benefício significativo de carreira com este curso

Melhores avaliações

Destaques
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 AIApr 24th 2018

This course was a good intro especially in setting all the necessary software for future courses. I suggest to read the manuals, books and other readings the profs suggest. The resources are helpful.

Instrutores

Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health

Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

Sobre 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....

Sobre o Programa de cursos integrados 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

Perguntas Frequentes – FAQ

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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