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所在平台: Udemy |
课程主页: https://www.udemy.com/course/r-programming-for-beginners-wl/
课程评论：没有评论
课程名称：初学者的R编程 课程概述：本课程涵盖了与学习和使用R编程语言进行数据分析和可视化相关的广泛基础主题。课程内容包括： 1. **R软件安装**：学习如何在计算机上安装R编程环境，这是入门R的第一步。 2. **基本语法**：了解如何编写和执行简单的R命令。 3. **变量定义**：学习如何创建和操作变量，以存储数据和数值。 4. **R中的运算符**：讲解各种运算符，包括算术运算符、比较运算符和逻辑运算符。 5. **条件语句**：学习如何使用条件语句（if-else）在R程序中根据特定条件做决策。 6. **循环**：介绍多种循环（如for循环和while循环），允许重复任务和操作。 7. **函数**：学习如何定义和使用R中的函数，以将代码封装为可重用的模块。 8. **数据结构**：介绍R中的各种数据结构，如向量、矩阵、数据框和列表。 9. **数据可视化**：学习如何使用R创建图形表示的数据可视化。 10. **描述性统计**：涵盖基本的描述性统计知识，包括均值、中位数、标准差等指标。 11. **统计分析**：介绍相关性、线性回归和逻辑回归等统计技术，以分析数据之间的关系并进行预测。 12. **数据接口**：学习如何从CSV文件导入数据并更改工作目录。 课程的总体目标是为初学者提供扎实的R编程和数据分析技术基础。完成课程后，学生将能够编写和理解R代码，使用循环、条件语句和函数编写程序，创建数据可视化，并进行统计分析。课程末尾的最终项目将帮助学生实践所学内容，通过数据分析让学生巩固技能并增强自信，以确保他们能够熟练应对课程之外的数据分析任务。
The "R Programming for Beginners" course covers a wide range of fundamental topics related to learning and using the R programming language for data analysis and visualization. Here's a breakdown of the main topics covered in the course:1. **Installing R software:** Students learn how to install the R programming environment on their computers, which is the first step in getting started with R.2. **Basic syntax:** The course covers the basic syntax of the R language, which includes understanding how to write and execute simple R commands.3. **Variable definition:** Students learn how to create and manipulate variables to store data and values in R.4. **Operators in R:** This topic covers various types of operators in R, including arithmetic, comparison, and logical operators.5. **Conditionals:** Students learn how to use conditional statements (if-else) to make decisions in their R programs based on certain conditions.6. **Loops:** The course covers different types of loops (such as for loops and while loops) that allow students to repeat tasks and operations.7. **Functions:** Students learn how to define and use functions in R, which allow them to encapsulate code into reusable blocks.8. **Data structures:** The course introduces various data structures in R, such as vectors, matrices, data frames, and lists.9. **Visualization of data:** Students learn how to create visualizations using R to represent data graphically.10. **Descriptive statistics:** The course covers essential descriptive statistics, including measures like mean, median, standard deviation, and more.11. **Statistical analysis:** Students are introduced to statistical techniques like correlation, linear regression, and logistic regression for analyzing relationships and making predictions from data.12. **Data interfaces:** The course likely covers how to import data from CSV and change working directory.The overall goal of the course is to provide beginners with a solid foundation in R programming and data analysis techniques. By the end of the course, students will be able to write and understand R code, write programs using loops, conditional statements and functions, create data visualizations, and conduct statistical analyses.At the end of the course there is a final project that will help people practise what they have learnt. This project requires students to analyse data, allowing students to practically apply their knowledge, bolstering their skills and confidence. This emphasis on real-world application ensures students can adeptly handle data analysis tasks beyond the course.
