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所在平台: Udemy |
课程主页: https://www.udemy.com/course/introduction-to-programming-r-a-modern-approach/
课程评论：没有评论
Coursera《R语言编程入门：现代化方法》课程总结 本课程专为初学者设计，旨在教授R语言编程。R语言是数据科学、数据分析和统计学领域的关键工具，因其简洁易学而备受青睐。 课程内容涵盖： * **R与RStudio的安装与基本使用**：从下载安装R及强大的RStudio集成开发环境开始。 * **R数据结构**：深入了解原子向量、列表、数据框和tibble等核心数据结构，学习如何创建和操作它们。 * **数据导入与处理**：掌握如何导入Excel和CSV文件，以及数据汇总、格式转换（长宽格式互转）等常用数据处理技巧。 * **函数创建与流程控制**：学习创建自定义函数，并掌握使用if-else语句进行代码逻辑控制。 * **提高效率**：学习RStudio的快捷键，以提升编程效率和生产力。 * **数据可视化**：内容包括Base R基础绘图及强大的ggplot2可视化包，帮助您创建具有洞察力且美观的图表。 * **数据分析管道**：通过`purrr`和`dplyr`包，学习构建强大、易读的数据分析流程（pipelines）。 课程强调R语言的易用性，并介绍了其开源的特性，鼓励学习者未来成为R的贡献者。通过本课程，学员将为在数据驱动的时代打下坚实的编程基础。
Are you nervous or excited about learning how to code? Are you a beginner who wants to get better at learning R the right way? Would you like to learn how to make cool looking and insightful charts? If so, you are in the right place.Learning how to code in R is an excellent way to start. R is one of the top languages used by data scientists, data analysts, statisticians, etc. The best thing about it is its simplicity.R was introduced to me in the summer of 2008 as an intern at a marketing firm; since then, I have been a loyal user. Along with SAS, I use it daily to conduct data analysis and reporting. R is one of my top go-to tools. I start with the basics showing you how I learned it, and then I teach it at a pace comfortable for a beginner.We are living in exciting times, and the future looks bright for those skilled in programming. Industries are using data more and more to make crucial decisions. They need experienced analysts to help design data collection processes and to analyze it. Where do you fit in this picture now and tomorrow? Learning R sets you now and will sustain you for the future.R was designed mainly for statisticians or those who did not have a computer science background, hence its intuitiveness. R is a free and open-source programming language. It will not cost you anything to have R installed and running on your computer. R is open-source, meaning that contributors can improve its usability by creating packages. Packages contain functions to help users solve specific problems that R's founders did not think of. It would be a pleasure to see you grow to become a contributor to R someday.Although R itself is mighty, it is not the best place to write R codes. We will write R codes (or scripts) in R studio. R studio is a powerful editor for R. You will learn all about it in this course.Here are some of the things you will learn in this course:1. Download and install R and R studio2. The different data structures, such as atomic vectors, lists, data frames, and tibbles. How to create and use them3. How to import an excel or a CSV file into R4. Create functions5. How to execute chunks of code following an if-else logic6. Lean R studio short cut keys to increase your efficiency and productivity7. How to summarize data8. How to transpose data from long format to wide format and backward9. How to create powerful easy to read pipelines using purrr and dplyr packages10. Introduction to base R plots11. Ggplots12. And moreThanks for taking the time to check out my course. I cannot wait to help you get started with R and R studio. If you have any questions, please message me or check out the free preview lecture to learn more.
