About this Course
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Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 8 hours to complete

Suggested: 1-4 hours/week...

English

Subtitles: Arabic, French, Chinese (Simplified), Greek, Italian, Portuguese (Brazilian), Vietnamese, Russian, Turkish, English, Hebrew, Spanish, Japanese...

What you will learn

  • Check

    Create a Github repository

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    Explain essential study design concepts

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

  • Check

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

Skills you will gain

Data ScienceGithubR ProgrammingRstudio

Course 1 of 10 in the

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 8 hours to complete

Suggested: 1-4 hours/week...

English

Subtitles: Arabic, French, Chinese (Simplified), Greek, Italian, Portuguese (Brazilian), Vietnamese, Russian, Turkish, English, Hebrew, Spanish, Japanese...

Syllabus - What you will learn from this course

Week
1
2 hours to complete

Week 1

16 videos (Total 51 min), 5 readings, 1 quiz
16 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
5 readings
Welcome to the Data Scientist's Toolbox10m
Pre-Course Survey10m
Syllabus10m
Specialization Textbooks10m
The Elements of Data Analytic Style10m
1 practice exercise
Week 1 Quiz10m
Week
2
1 hour to complete

Week 2: Installing the Toolbox

9 videos (Total 51 min), 1 quiz
9 videos
Command Line Interface16m
Introduction to Git4m
Introduction to Github3m
Creating a Github Repository5m
Basic Git Commands5m
Basic Markdown2m
Installing R Packages5m
Installing Rtools2m
1 practice exercise
Week 2 Quiz10m
Week
3
1 hour to complete

Week 3: Conceptual Issues

4 videos (Total 35 min), 1 quiz
4 videos
What is Data?5m
What About Big Data?4m
Experimental Design15m
1 practice exercise
Week 3 Quiz10m
Week
4
2 hours to complete

Week 4: Course Project Submission & Evaluation

1 reading, 1 quiz
1 reading
Post-Course Survey10m
4.5
4088 ReviewsChevron Right

38%

started a new career after completing these courses

35%

got a tangible career benefit from this course

Top reviews from The Data Scientist’s Toolbox

Highlights
Introductory course
(1056)
Foundational tools
(243)
By 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.

By 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.

Instructors

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Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

About 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....

About the Data Science Specialization

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

Frequently Asked 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.

More questions? Visit the Learner Help Center.