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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-with-r-tidyverse/
课程评论：没有评论
课程名称：使用R语言的资料科学：tidyverse 课程概述：资料科学技能在当前就业市场上仍然是最受欢迎的技能之一。许多人只关注资料科学的有趣部分，例如：“寻找数据洞察”，“揭示数据背后的隐秘真相”，“构建预测模型”，“应用机器学习算法”等。然而，对于大多数资料科学家来说，处理实际数据时，任何资料科学项目中最耗时的操作实际上是：“数据导入”，“数据清理”，“数据整合”，“数据探索”等。因此，拥有一个适合的工具来处理相关的数据任务是十分必要的。R语言作为在应用统计、资料科学和数据探索等领域中最受欢迎的编程语言之一，与R的库集合tidyverse结合，即可形成一个强大的工具，旨在处理资料科学相关任务。所有tidyverse库共享独特的哲学、语法和数据类型，因此这些库可以并行使用，使得您能够编写高效且优化的R代码，从而更快地完成项目。 本课程包括多个章节，每个章节介绍与数据相关任务的不同方面，以及相应的tidyverse工具帮助您处理特定任务。同时，课程结合了相关主题的理论与在R中处理的实际案例。在学习过程中，您将会面对许多不同的资料科学挑战，其中包括但不限于：如何使用tidyverse清理数据、数据整合的语法、如何使用dplyr和tidyr整合数据、创建类似于表格的对象tibble、使用readr和其他库导入和解析数据、利用stringr处理字符串、应用正则表达式概念处理字符串、使用forcats处理分类变量、数据可视化语法、使用ggplot2探索数据和绘制统计图表，使用purrr进行函数式编程及映射函数、利用purrr高效处理列表、关系数据的实际应用、使用dplyr处理关系数据、tidyverse中的整洁评估以及为最终的实用资料科学项目应用tidyverse工具。 课程内容包括：25小时以上的讲座视频、R脚本及额外的数据（在课程材料中提供）、每个章节末尾的作业以及作业解析视频（您可以查看自己的结果）。这一切使得本课程成为Udemy中最全面的R和tidyverse相关资料科学课程之一。今天就报名，成为R的tidyverse大师吧！
Data Science skills are still one of the most in-demand skills on the job market today. Many people see only the fun part of data science, tasks like: "search for data insight", "reveal the hidden truth behind the data", "build predictive models", "apply machine learning algorithms", and so on. The reality, which is known to most data scientists, is, that when you deal with real data, the most time-consuming operations of any data science project are: "data importing", "data cleaning", "data wrangling", "data exploring" and so on. So it is necessary to have an adequate tool for addressing given data-related tasks. What if I say, there is a freely accessible tool, that falls into the provided description above! R is one of the most in-demand programming languages when it comes to applied statistics, data science, data exploration, etc. If you combine R with R's collection of libraries called tidyverse, you get one of the deadliest tools, which was designed for data science-related tasks. All tidyverse libraries share a unique philosophy, grammar, and data types. Therefore libraries can be used side by side, and enable you to write efficient and more optimized R code, which will help you finish projects faster.This course includes several chapters, each chapter introduces different aspects of data-related tasks, with the proper tidyverse tool to help you deal with a given task. Also, the course brings to the table theory related to the topic, and practical examples, which are covered in R. If you dive into the course, you will be engaged with many different data science challenges, here are just a few of them from the course:Tidy data, how to clean your data with tidyverse?Grammar of data wrangling.How to wrangle data with dplyr and tidyr.Create table-like objects called tibble.Import and parse data with readr and other libraries.Deal with strings in R using stringr.Apply Regular Expressions concepts when dealing with strings.Deal with categorical variables using forcats.Grammar of Data Visualization.Explore data and draw statistical plots using ggplot2.Use concepts of functional programming, and map functions using purrr.Efficiently deal with lists with the help of purrr.Practical applications of relational data.Use dplyr for relational data.Tidy evaluation inside tidyverse.Apply tidyverse tools for the final practical data science project.Course includes:over 25 hours of lecture videos,R scripts and additional data (provided in the course material),engagement with assignments at the end of each chapter,assignments walkthrough videos (where you can check your results).All being said this makes one of Udemy's most comprehensive courses for data science-related tasks using R and tidyverse.Enroll today and become the master of R's tidyverse!!!
