When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

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.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

R Programming: Data Analysis and Modeling

R Programming: Data Analysis and Modeling

本课程是 R Programming for Data Science 专项课程的一部分

位教师：Bill Rosenthal

包含在中

了解更多

5个模块

深入了解一个主题并学习基础知识。

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

5个模块

深入了解一个主题并学习基础知识。

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

In this course, you'll manage, analyze, and visualize data in R; and create statistical and machine learning models from that data.

您将获得的技能

您将学习的工具

要了解的详细信息

可分享的证书

添加到您的领英档案

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 R Programming for Data Science 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有5个模块

To round out your R programming skills, you'll dive into its data science capabilities by loading and saving data and manipulating data frames using base R and the dplyr package. You'll also analyze data by exploring its underlying distribution and identifying missing values. Then, you'll visualize data by using base R and ggplot2 to plot that data in various ways. Lastly, you'll create statistical and machine learning models in R that can make predictions and other estimations about data.

单元详情

Up until now, you've mostly been applying the fundamentals of R as a general programming language. But, as you know, data science is where R really shines. In this lesson, you'll begin using R in a more data-driven context, particularly by managing data in various ways. This data-driven approach will continue throughout the rest of the course as you work toward building statistical and machine learning models.

涵盖的内容

1篇阅读材料7个插件

Now that you've loaded and shaped your data, you can begin analyzing it in earnest. In this lesson, you'll use R to apply various techniques—both statistical and otherwise—that will reveal useful insights about your data.

涵盖的内容

5个插件

Data analysis is not just about looking at raw numbers or text. Transforming your data into graphs and plots can greatly enhance your ability to interpret the data, as well as present that data to an audience. In this lesson, you'll use R to analyze your data from a visual perspective in order to reveal insights that raw numbers alone may not provide.

涵盖的内容

6个插件

In many data science projects, the ultimate goal is to create a model of the data. The model can be used to estimate some aspect of the data and the larger domain that the data is about. It can even be used to make predictions from the data, which is particularly attractive to businesses. In this lesson you'll get a crash course on modeling data, as well as how to implement those concepts in R.