About this Course
4.5
2,886 ratings
428 reviews
Specialization

Course 5 of 10 in the

100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Hours to complete

Approx. 10 hours to complete

Suggested: 4-9 hours/week...
Available languages

English

Subtitles: English, Vietnamese

What you will learn

  • Check

    Determine the reproducibility of analysis project

  • Check

    Organize data analysis to help make it more reproducible

  • Check

    Publish reproducible web documents using Markdown

  • Check

    Write up a reproducible data analysis using knitr

Skills you will gain

KnitrData AnalysisR ProgrammingMarkup Language
Specialization

Course 5 of 10 in the

100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Hours to complete

Approx. 10 hours to complete

Suggested: 4-9 hours/week...
Available languages

English

Subtitles: English, Vietnamese

Syllabus - What you will learn from this course

Week
1
Hours to complete
2 hours to complete

Week 1: Concepts, Ideas, & Structure

This week will cover the basic ideas of reproducible research since they may be unfamiliar to some of you. We also cover structuring and organizing a data analysis to help make it more reproducible. I recommend that you watch the videos in the order that they are listed on the web page, but watching the videos out of order isn't going to ruin the story. ...
Reading
9 videos (Total 72 min), 3 readings, 1 quiz
Video9 videos
What is Reproducible Research About?8m
Reproducible Research: Concepts and Ideas (part 1)7m
Reproducible Research: Concepts and Ideas (part 2) 5m
Reproducible Research: Concepts and Ideas (part 3) 3m
Scripting Your Analysis 4m
Structure of a Data Analysis (part 1)12m
Structure of a Data Analysis (part 2)17m
Organizing Your Analysis11m
Reading3 readings
Syllabus10m
Pre-course survey10m
Course Book: Report Writing for Data Science in R10m
Quiz1 practice exercise
Week 1 Quiz20m
Week
2
Hours to complete
3 hours to complete

Week 2: Markdown & knitr

This week we cover some of the core tools for developing reproducible documents. We cover the literate programming tool knitr and show how to integrate it with Markdown to publish reproducible web documents. We also introduce the first peer assessment which will require you to write up a reproducible data analysis using knitr. ...
Reading
9 videos (Total 59 min), 2 quizzes
Video9 videos
Markdown5m
R Markdown6m
R Markdown Demonstration7m
knitr (part 1)7m
knitr (part 2) 4m
knitr (part 3) 4m
knitr (part 4) 9m
Introduction to Course Project 14m
Quiz1 practice exercise
Week 2 Quiz10m
Week
3
Hours to complete
1 hour to complete

Week 3: Reproducible Research Checklist & Evidence-based Data Analysis

This week covers what one could call a basic check list for ensuring that a data analysis is reproducible. While it's not absolutely sufficient to follow the check list, it provides a necessary minimum standard that would be applicable to almost any area of analysis....
Reading
10 videos (Total 60 min)
Video10 videos
RPubs 3m
Reproducible Research Checklist (part 1)8m
Reproducible Research Checklist (part 2) 10m
Reproducible Research Checklist (part 3) 6m
Evidence-based Data Analysis (part 1)3m
Evidence-based Data Analysis (part 2) 3m
Evidence-based Data Analysis (part 3) 4m
Evidence-based Data Analysis (part 4) 4m
Evidence-based Data Analysis (part 5) 7m
Week
4
Hours to complete
3 hours to complete

Week 4: Case Studies & Commentaries

This week there are two case studies involving the importance of reproducibility in science for you to watch....
Reading
5 videos (Total 59 min), 1 reading, 1 quiz
Video5 videos
Case Study: Air Pollution14m
Case Study: High Throughput Biology30m
Commentaries on Data Analysis2m
Introduction to Peer Assessment 232s
Reading1 reading
Post-Course Survey10m
4.5
428 ReviewsChevron Right
Career direction

35%

started a new career after completing these courses
Career Benefit

31%

got a tangible career benefit from this course

Top Reviews

By AAFeb 13th 2016

My favorite course, at least it gives me an argument why scripted statistics is awesome and can be applied to a number of data related activities. Recycling chunks of code has proven useful to me.

By ASJun 23rd 2017

Of course, I liked this course. There was even an extra non-graded assignment. Plus two graded assignments. Quality instruction videos and lots of practice. Everything a learner needs.

Instructors

Avatar

Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Jeff Leek, 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.