About this Course
4.7
4,124 ratings
607 reviews
Specialization

Course 4 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. 15 hours to complete

Suggested: 5 hours/week...
Available languages

English

Subtitles: English, Vietnamese, Chinese (Simplified)

What you will learn

  • Check

    Apply cluster analysis techniques to locate patterns in data

  • Check

    Make graphical displays of very high dimensional data

  • Check

    Understand analytic graphics and the base plotting system in R

  • Check

    Use advanced graphing systems such as the Lattice system

Skills you will gain

Cluster AnalysisGgplot2R ProgrammingExploratory Data Analysis
Specialization

Course 4 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. 15 hours to complete

Suggested: 5 hours/week...
Available languages

English

Subtitles: English, Vietnamese, Chinese (Simplified)

Syllabus - What you will learn from this course

Week
1
Hours to complete
20 hours to complete

Week 1

This week covers the basics of analytic graphics and the base plotting system in R. We've also included some background material to help you install R if you haven't done so already. ...
Reading
15 videos (Total 109 min), 6 readings, 7 quizzes
Video15 videos
Installing R on Windows (3.2.1)3m
Installing R on a Mac (3.2.1)1m
Installing R Studio (Mac)3m
Setting Your Working Directory (Windows)7m
Setting Your Working Directory (Mac)7m
Principles of Analytic Graphics12m
Exploratory Graphs (part 1)9m
Exploratory Graphs (part 2) 5m
Plotting Systems in R9m
Base Plotting System (part 1)11m
Base Plotting System (part 2)6m
Base Plotting Demonstration16m
Graphics Devices in R (part 1)5m
Graphics Devices in R (part 2)7m
Reading6 readings
Welcome to Exploratory Data Analysis10m
Syllabus10m
Pre-Course Survey10m
Exploratory Data Analysis with R Book10m
The Art of Data Science10m
Practical R Exercises in swirl Part 110m
Quiz1 practice exercise
Week 1 Quiz20m
Week
2
Hours to complete
17 hours to complete

Week 2

Welcome to Week 2 of Exploratory Data Analysis. This week covers some of the more advanced graphing systems available in R: the Lattice system and the ggplot2 system. While the base graphics system provides many important tools for visualizing data, it was part of the original R system and lacks many features that may be desirable in a plotting system, particularly when visualizing high dimensional data. The Lattice and ggplot2 systems also simplify the laying out of plots making it a much less tedious process....
Reading
7 videos (Total 61 min), 1 reading, 6 quizzes
Video7 videos
Lattice Plotting System (part 2)6m
ggplot2 (part 1)6m
ggplot2 (part 2)13m
ggplot2 (part 3)9m
ggplot2 (part 4)10m
ggplot2 (part 5)8m
Reading1 reading
Practical R Exercises in swirl Part 210m
Quiz1 practice exercise
Week 2 Quiz20m
Week
3
Hours to complete
13 hours to complete

Week 3

Welcome to Week 3 of Exploratory Data Analysis. This week covers some of the workhorse statistical methods for exploratory analysis. These methods include clustering and dimension reduction techniques that allow you to make graphical displays of very high dimensional data (many many variables). We also cover novel ways to specify colors in R so that you can use color as an important and useful dimension when making data graphics. All of this material is covered in chapters 9-12 of my book Exploratory Data Analysis with R....
Reading
12 videos (Total 77 min), 1 reading, 4 quizzes
Video12 videos
Hierarchical Clustering (part 2)5m
Hierarchical Clustering (part 3)7m
K-Means Clustering (part 1)5m
K-Means Clustering (part 2)4m
Dimension Reduction (part 1)7m
Dimension Reduction (part 2)9m
Dimension Reduction (part 3)6m
Working with Color in R Plots (part 1)4m
Working with Color in R Plots (part 2)7m
Working with Color in R Plots (part 3)6m
Working with Color in R Plots (part 4)3m
Reading1 reading
Practical R Exercises in swirl Part 310m
Week
4
Hours to complete
6 hours to complete

Week 4

This week, we'll look at two case studies in exploratory data analysis. The first involves the use of cluster analysis techniques, and the second is a more involved analysis of some air pollution data. How one goes about doing EDA is often personal, but I'm providing these videos to give you a sense of how you might proceed with a specific type of dataset. ...
Reading
2 videos (Total 55 min), 2 readings, 2 quizzes
Video2 videos
Air Pollution Case Study40m
Reading2 readings
Practical R Exercises in swirl Part 410m
Post-Course Survey10m
4.7
607 ReviewsChevron Right
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37%

started a new career after completing these courses
Career Benefit

83%

got a tangible career benefit from this course
Career promotion

18%

got a pay increase or promotion

Top Reviews

By YSep 24th 2017

Very good course! It provide me the foundation in learning how to plot and interpret data. This will definitely strengthen my "R programming" to generate publication type figure for my genomics data!

By CCJul 29th 2016

This is the second course I have taken from Roger Peng and both were outstanding. I have a strong math background, but not much of a background in stats, but this course was very approachable for me.

Instructors

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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.