About this Course
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다음의 4/10개 강좌

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탄력적인 마감일

일정에 따라 마감일을 재설정합니다.

완료하는 데 약 15시간 필요

영어

자막: 영어, 베트남어, 중국어 (간체자)

배울 내용

  • 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

귀하가 습득할 기술

Cluster AnalysisGgplot2R ProgrammingExploratory Data Analysis

다음의 4/10개 강좌

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

탄력적인 마감일

일정에 따라 마감일을 재설정합니다.

완료하는 데 약 15시간 필요

영어

자막: 영어, 베트남어, 중국어 (간체자)

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 20시간 필요

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. ...
15 videos (Total 109 min), 6 readings, 7 quizzes
15개의 동영상
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
6개의 읽기 자료
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
1개 연습문제
Week 1 Quiz20m
2
완료하는 데 17시간 필요

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....
7 videos (Total 61 min), 1 reading, 6 quizzes
7개의 동영상
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
1개의 읽기 자료
Practical R Exercises in swirl Part 210m
1개 연습문제
Week 2 Quiz20m
3
완료하는 데 13시간 필요

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....
12 videos (Total 77 min), 1 reading, 4 quizzes
12개의 동영상
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
1개의 읽기 자료
Practical R Exercises in swirl Part 310m
4
완료하는 데 6시간 필요

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. ...
2 videos (Total 55 min), 2 readings, 2 quizzes
2개의 동영상
Air Pollution Case Study40m
2개의 읽기 자료
Practical R Exercises in swirl Part 410m
Post-Course Survey10m
4.7
652개의 리뷰Chevron Right

37%

이 강좌를 수료한 후 새로운 경력 시작하기

38%

이 강좌를 통해 확실한 경력상 이점 얻기

15%

급여 인상 또는 승진하기

최상위 리뷰

대학: 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!

대학: 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.

강사

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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

존스홉킨스대학교 정보

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....

데이터 과학 전문 분야 정보

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....
데이터 과학

자주 묻는 질문

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  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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