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所在平台: Udemy |
课程主页: https://www.udemy.com/course/basics-of-r-software-for-data-science/
课程评论：没有评论
**课程名称：** R语言基础：数据科学入门 **课程概述：** 本课程将介绍R语言，一款开源、功能强大且组织完善的软件包，能够极大地促进数据分析、建模、推断性测试和预测。R语言用户友好，允许用户创建新的函数命令来解决统计问题，并可运行于多种UNIX平台（包括LINUX）、Windows和Mac OS。 R是目前分析和数据科学领域最受欢迎的开源语言。微软的数据科学家利用R语言，将机器学习应用于Bing、Azure、Office以及销售、市场营销和财务部门的数据。Twitter也使用R来评估用户体验。此外，R的多平台兼容性及处理大规模复杂数据集的能力，使其成为学术界在实验室中进行数据分析的理想工具。 R的应用广泛，可用于简单计算、矩阵计算、微分方程、优化、统计分析、绘图等。对于希望进行大量统计计算和数据可视化的用户来说，R也非常有用。 数据分析离不开统计学。获取数据后，任何统计分析都始于描述性统计，旨在挖掘数据中隐藏的信息。描述性统计的工具基于数学和统计函数，需要通过软件进行计算。市面上存在付费和免费的统计软件，而R是其中一款备受欢迎的免费统计软件。本课程的目标是教授描述性统计的基本工具，以及如何使用R软件进行描述性统计分析。 **课程大纲：** 无
R is an open source software - a well organized and sophisticated package - that facilitates data analysis, modelling, inferential testing and forecasting. It is a user friendly software which allows to create new function commands to solve statistical problems. It runs on a variety of UNIX platforms (and similar systems such as LINUX), Windows and Mac OS.R is the most preferred open-source language for analytics and data science. At Microsoft, R is used by its data scientists, who apply machine learning to data from Bing, Azure, Office, and the Sales, Marketing, and Finance departments. Twitter has been using R for measuring user-experience. On the other hand, the cross-platform compatibility of R and its capacity to handle large and complex data sets make it an ideal tool for academicians to analyze data in their labs.R can be used for simple calculations, matrix calculations, differential equations, optimisation, statistical analysis, plotting graphs, etc. Also, it is useful to anybody who wishes to undertake extensive statistical computations and data visualization.Any data analysis is incomplete without statistics. After getting the data, any statistical analysis starts with descriptive statistics which aims to extract the information hidden inside the data. The tools of descriptive statistics are based on mathematical and statistical functions which are to be evaluated using the software. The statistical software are paid as well as free. Most of the statistical software are paid software. A popular free statistical software is R. What are the basic tools of descriptive statistics and how to use the R software for descriptive statistical analysis is the objective of the course to be taught.
