开始时间: 12/21/2023 持续时间: Approximately 7 months to complete Suggested pace of 3 hours/week
所在平台: Coursera专项课程 课程类别: 其他类别 大学或机构: CourseraNew |
课程主页: https://www.coursera.org/specializations/applied-data-science-r
课程评论:没有评论
Shiny DashboardsData Analysis and ModellingR Programmin LanguageData Visualization (DataViz)SQL & RDBMSData ScienceR ProgrammingSelect (Sql)Relational Databases (RDBMS)Tables (Database)Statistical AnalysisData Analysis
Course Link: https://www.coursera.org/learn/introducton-r-programming-data-science
Name:Introduction to R Programming for Data Science
Description:Offered by IBM. When working in the data science field you will definitely become acquainted with the R language and the role it plays in ... Enroll for free.
Course Link: https://www.coursera.org/learn/sql-data-science-r
Name:SQL for Data Science with R
Description:Offered by IBM. Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for ... Enroll for free.
Course Link: https://www.coursera.org/learn/data-analysis-with-r
Name:Data Analysis with R
Description:Offered by IBM. The R programming language is purpose-built for data analysis. R is the key that opens the door between the problems that ... Enroll for free.
Course Link: https://www.coursera.org/learn/data-visualization-r
Name:Data Visualization with R
Description:Offered by IBM. In this course, you will learn the Grammar of Graphics, a system for describing and building graphs, and how the ggplot2 ... Enroll for free.
Course Link: https://www.coursera.org/learn/data-science-with-r-capstone-project
Name:Data Science with R - Capstone Project
Description:Offered by IBM. In this capstone course, you will apply various data science skills and techniques that you have learned as part of the ... Enroll for free.
使用 R 的应用数据科学专项课程(Applied Data Science with R Specialization),用 R 和 SQL 打造你的数据科学技能,掌握将数据转化为信息和见解的能力。您将学到什么:执行基本的 R 编程任务,如处理数据结构、数据操作、使用 API、网络抓取以及使用 R Studio 和 Jupyter;使用 JupyterLab 创建关系数据库和表格,从 CSV 文件加载数据,并使用 SQL 和 R 查询数据;完成数据分析过程,包括数据准备、统计分析和预测建模、统计分析和预测建模;使用 ggplot、leaflet 和 R Shiny 等库,用数据可视化图表、绘图和仪表板来传达数据分析结果。