À propos de ce cours
4.5
15,492 ratings
•
3,228 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....
Stacks

Cours 1 sur 10 dans la

Spécialisation Data Science
Globe

Cours en ligne à 100 %

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Calendar

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Clock

Recommandé : 1-4 hours/week

Approx. 8 heures pour terminer
Comment Dots

English

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

Ce que vous allez apprendre

  • 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

Compétences que vous acquerrez

GithubRstudioData ScienceR Programming
Stacks

Cours 1 sur 10 dans la

Spécialisation Data Science
Globe

Cours en ligne à 100 %

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Calendar

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Clock

Recommandé : 1-4 hours/week

Approx. 8 heures pour terminer
Comment Dots

English

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

Programme du cours : ce que vous apprendrez dans ce cours

1

Section
Clock
2 heures pour terminer

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 vidéos (Total 51 min), 5 lectures, 1 quiz
Video16 vidéos
Specialization Motivation12 min
The Data Scientist's Toolbox5 min
Getting Help8 min
Finding Answers4 min
R Programming Overview2 min
Getting Data Overview1 min
Exploratory Data Analysis Overview1 min
Reproducible Research Overview1 min
Statistical Inference Overview1 min
Regression Models Overview1 min
Practical Machine Learning Overview1 min
Building Data Products Overview1 min
Installing R on Windows {Roger Peng}3 min
Install R on a Mac {Roger Peng}2 min
Installing Rstudio {Roger Peng}1 min
Installing Outside Software on Mac (OS X Mavericks)1 min
Reading5 lectures
Welcome to the Data Scientist's Toolbox10 min
Pre-Course Survey10 min
Syllabus10 min
Specialization Textbooks10 min
The Elements of Data Analytic Style10 min
Quiz1 exercice pour s'entraîner
Week 1 Quiz10 min

2

Section
Clock
1 heure pour terminer

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 vidéos (Total 51 min), 1 quiz
Video9 vidéos
Tips from Coursera Users - Optional Video 3 min
Command Line Interface16 min
Introduction to Git4 min
Introduction to Github3 min
Creating a Github Repository5 min
Basic Git Commands5 min
Basic Markdown2 min
Installing R Packages5 min
Installing Rtools2 min
Quiz1 exercice pour s'entraîner
Week 2 Quiz10 min

3

Section
Clock
1 heure pour terminer

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 vidéos (Total 35 min), 1 quiz
Video4 vidéos
Types of Questions9 min
What is Data?5 min
What About Big Data?4 min
Experimental Design15 min
Quiz1 exercice pour s'entraîner
Week 3 Quiz10 min

4

Section
Clock
2 heures pour terminer

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 lecture, 1 quiz
Reading1 lecture
Post-Course Survey10 min
4.5
Direction Signs

36%

a commencé une nouvelle carrière après avoir terminé ces cours
Briefcase

83%

a bénéficié d'un avantage concret dans sa carrière grâce à ce cours

Meilleurs avis

Points forts
Introductory course
(1056)
Foundational tools
(243)
par LR•Sep 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.

par AI•Apr 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.

Enseignants

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

À propos 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....

À propos de la Spécialisation 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

Foire Aux Questions

  • 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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