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Data Science 专项课程

Johns Hopkins University

课程信息

4.7

3,832 ratings

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577 reviews

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data....

立即开始，按照自己的计划学习。

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完成时间大约为15 小时

字幕：English, Chinese (Simplified)

- Apply cluster analysis techniques to locate patterns in data
- Make graphical displays of very high dimensional data
- Understand analytic graphics and the base plotting system in R
- Use advanced graphing systems such as the Lattice system

Exploratory Data AnalysisGgplot2R ProgrammingCluster Analysis

立即开始，按照自己的计划学习。

根据您的日程表重置截止日期。

完成时间大约为15 小时

字幕：English, Chinese (Simplified)

章节

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 个视频（共 109 分钟）, 6 个阅读材料, 7 个测验

Introduction1分钟

Installing R on Windows (3.2.1)3分钟

Installing R on a Mac (3.2.1)1分钟

Installing R Studio (Mac)3分钟

Setting Your Working Directory (Windows)7分钟

Setting Your Working Directory (Mac)7分钟

Principles of Analytic Graphics12分钟

Exploratory Graphs (part 1)9分钟

Exploratory Graphs (part 2) 5分钟

Plotting Systems in R9分钟

Base Plotting System (part 1)11分钟

Base Plotting System (part 2)6分钟

Base Plotting Demonstration16分钟

Graphics Devices in R (part 1)5分钟

Graphics Devices in R (part 2)7分钟

Welcome to Exploratory Data Analysis10分钟

Syllabus10分钟

Pre-Course Survey10分钟

Exploratory Data Analysis with R Book10分钟

The Art of Data Science10分钟

Practical R Exercises in swirl Part 110分钟

Week 1 Quiz20分钟

章节

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 个视频（共 61 分钟）, 1 个阅读材料, 6 个测验

Lattice Plotting System (part 2)6分钟

ggplot2 (part 1)6分钟

ggplot2 (part 2)13分钟

ggplot2 (part 3)9分钟

ggplot2 (part 4)10分钟

ggplot2 (part 5)8分钟

Practical R Exercises in swirl Part 210分钟

Week 2 Quiz20分钟

章节

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 个视频（共 77 分钟）, 1 个阅读材料, 4 个测验

Hierarchical Clustering (part 2)5分钟

Hierarchical Clustering (part 3)7分钟

K-Means Clustering (part 1)5分钟

K-Means Clustering (part 2)4分钟

Dimension Reduction (part 1)7分钟

Dimension Reduction (part 2)9分钟

Dimension Reduction (part 3)6分钟

Working with Color in R Plots (part 1)4分钟

Working with Color in R Plots (part 2)7分钟

Working with Color in R Plots (part 3)6分钟

Working with Color in R Plots (part 4)3分钟

Practical R Exercises in swirl Part 310分钟

章节

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 个视频（共 55 分钟）, 2 个阅读材料, 2 个测验

Practical R Exercises in swirl Part 410分钟

Post-Course Survey10分钟

4.7

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创建者 Y•Sep 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!

创建者 CC•Jul 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.

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....

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....

When will I have access to the lectures and assignments?

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.

What will I get if I subscribe to this Specialization?

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.

What is the refund policy?

Is financial aid available?

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