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所在平台: Udemy |
课程主页: https://www.udemy.com/course/r-programming-course-for-absolute-beginners/
课程评论：没有评论
课程名称：R编程入门 课程概述：如果你决定学习R作为你的数据科学编程语言，你做出了一个很好的选择！R是最广泛使用的统计编程工具，功能强大、灵活且易于使用，是成千上万数据分析师在公司和学术界的首选工具。这门课程将帮助你在短时间内掌握R的基础知识，为成为一名熟练的R数据科学家奠定第一步。课程专为初学者设计，因此你无需在开始之前了解R（甚至不需要在计算机上安装R程序；我会教你如何安装）。完成课程后，你将掌握最重要的R编程技能，并能够通过实践进一步发展这些技能，基于你在课程中学到的知识。 课程包含约100个视频讲座，共分为九个部分。在课程的第一部分，你将开始学习R：安装程序（如果你还没有安装的话）、熟悉R Studio的工作界面，以及学习一些基本的技术内容，如安装和激活包、设置工作目录。此外，你还将学习在R中执行简单操作和如何处理变量。 接下来的五个部分将专注于R中的五种数据结构：向量、矩阵、列表、因子和数据框。你将学习如何操作数据结构：如何索引、编辑数据，如何根据不同标准筛选数据，如何创建和修改对象（或变量），如何对数据应用函数等等。这些是非常重要的主题，因为R是一个统计计算软件，大部分R编程都是关于数据处理的。因此，在进行更高级的统计分析之前，你必须掌握基础的数据处理技巧。 完成数据结构后，我们将进入R中的编程结构部分。在这一部分，你将学习循环、条件语句和函数。你将学习如何将循环和条件语句结合起来执行复杂任务，以及如何创建可保存和重复使用的自定义函数。我们还将学习一些函数的实际示例。 接下来的部分将讨论字符串的处理。我们将涵盖一些最实用的函数，帮助你操作字符串。因此，你将学习如何格式化字符串用于打印、如何连接字符串、如何从给定字符串中提取子字符串，以及如何创建识别字符串模式的正则表达式。 在后续部分中，你将学习如何在R中绘制图表。我们将覆盖七种类型的图表：点图（散点图）、折线图、条形图、饼图、直方图、密度线和箱线图。此外，你将学习如何绘制单变量函数的图像以及如何导出所创建的图表。每个命令和函数都有视觉解释：你可以实时查看输出。每个部分末尾将提供PDF文件，包含实用练习，帮助你应用和巩固所学知识。 如果你想从零开始学习R，这门课程就是你的最佳选择。立即注册，开启你精彩的R编程之旅吧！
If you have decided to learn R as your data science programming language, you have made an excellent decision! R is the most widely used tool for statistical programming. It is powerful, versatile and easy to use. It is the first choice for thousands of data analysts working in both companies and academia. This course will help you master the basics of R in a short time, as a first step to become a skilled R data scientist. The course is meant for absolute beginners, so you don't have to know anything about R before starting. (You don't even have to have the R program on your computer; I will show you how to install it.) But after graduating this course you will have the most important R programming skills - and you will be able to further develop these skills, by practicing, starting from what you will have learned in the course. This course contains about 100 video lectures in nine sections. In the first section of this course you will get started with R: you will install the program (in case you didn't do it already), you will familiarize with the working interface in R Studio and you will learn some basic technical stuff like installing and activating packages or setting the working directory. Moreover, you will learn how to perform simple operations in R and how to work with variables. The next five sections will be dedicated to the five types of data structures in R: vectors, matrices, lists, factors and data frames. So you'll learn how to manipulate data structures: how to index them, how to edit data, how to filter data according to various criteria, how to create and modify objects (or variables), how to apply functions to data and much more. These are very important topics, because R is a software for statistical computing and most of the R programming is about manipulating data. So before getting to more advanced statistical analyses in R you must know the basic techniques of data handling. After finishing with the data structures we'll get to the programming structures in R. In this section you'll learn about loops, conditional statements and functions. You'll learn how to combine loops and conditional statements to perform complex tasks, and how to create custom functions that you can save and reuse later. We will also study some practical examples of functions. The next section is about working with strings. Here we will cover the most useful functions that allow us to manipulate strings. So you will learn how to format strings for printing, how to concatenate strings, how to extract substrings from a given string and especially how to create regular expressions that identify patterns in strings. In the following section you'll learn how to build charts in R. We are going to cover seven types of charts: dot chart (scatterplot), line chart, bar chart, pie chart, histogram, density line and boxplot. Moreover, you will learn how to plot a function of one variable and how to export the charts you create. Every command and function is visually explained: you can see the output live. At the end of each section you will find a PDF file with practical exercises that allow you to apply and strengthen your knowledge. So if you want to learn R from scratch, you need this course. Enroll right now and begin a fantastic R programming journey!
