|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/500-r-programming-basic-to-advanced-question-practice-tests/
课程评论：没有评论
课程名称：完整的R编程基础到高级考试 - 所有主题 课程概述：经验是人们对他们错误的称呼。欢迎参加“完整的R编程基础到高级考试 - 所有主题”课程。本课程涵盖了R编程的基本知识和高级技术，分为几个章节： 1. **R编程基础**：介绍R语言的基本概念，系统安装与配置，以及R控制台的使用，为后续的数据分析和统计计算打下基础。 2. **数据导入与处理**：深入核心数据类型，了解数据在R中的结构与操作，学习从不同来源导入数据，以便高效管理和分析。 3. **数据存储、格式、对象与操作**：探讨R如何处理数据存储与各种数据格式，掌握子集技术和向量化操作，获得有效的数据管理与操作能力。 4. **控制结构、函数、作用域规则、循环函数与调试**：讲解编写高效有序代码的基本概念，包括控制结构、函数创建与使用、变量作用域及调试技巧。 5. **性能分析、模拟与数据分析**：学习高级的数据分析技术，包括模拟复杂系统的能力，使用R分析器优化代码性能，以及数据清理和探索性数据分析(EDA)。 6. **命令、包、数据可视化与线性回归**：掌握R命令和如何利用包扩展R的功能，学习多种绘图技术进行数据可视化，以及线性回归的基本统计方法。 7. **分布、图形与神经网络**：了解R内置的统计分布，使用其强大的可视化工具创建复杂图形，并简要介绍神经网络这一高级机器学习技术。 通过本课程，您将获得R编程的全面知识，能够有效地进行数据分析和处理。
Experience is the name Everyone gives to their Mistakes.Welcome to the The Complete R Programming Basic to Advanced Exam-All TopicsExam SyllabusBasics and Fundamentals of R ProgrammingIn this Chapter, we cover the essentials of R programming, including a basic overview of the R language, how to install and configure R on your system, and an introduction to using the R console for input and evaluation. This foundation will prepare you to work with R effectively for data analysis and statistical computing.Nuts and Bolts and Getting Data In and OutIn this Chapter, we will dive into the core data types in R, giving you a solid understanding of how data is structured and manipulated within the language. We'll also explore how to read datasets into R from various sources, ensuring you can efficiently import and manage data for analysis. This chapter equips you with the fundamental skills needed to handle data in R.R - Data Storage, Formats, Objects and OperationsIn this Chapter, we will explore how R handles data storage and various data formats, with a focus on textual data. You'll learn about subsetting techniques to efficiently access and manipulate parts of your data, and we'll delve into vectorized operations, which allow you to perform calculations on entire datasets at once. This chapter provides the tools needed to manage and operate on data in R effectively.Control Structures, Functions, Scoping Rules, Loop Functions and DebuggingIn this Chapter, we will dive into the essential programming concepts that allow you to write efficient and organized R code. You'll learn about control structures like if, else, for, and while loops to direct the flow of your programs, how to create and use functions, and the scoping rules that determine how variables are accessed within your code. Additionally, we'll cover loop functions for applying operations across datasets and debugging techniques to troubleshoot and refine your R scripts.Profiling, Simulation and Data AnalysisIn this Chapter, we will explore advanced techniques to enhance your data analysis skills in R. You'll learn how to perform simulations to model and understand complex systems, use the R profiler to optimize your code's performance, and master data wrangling techniques to clean and prepare your data for analysis. We'll also cover exploratory data analysis (EDA), enabling you to uncover patterns, trends, and insights within your data.Commands, Packages, Visualizing Data and Linear RegressionIn this Chapter, we will over essential R commands and explore how to leverage packages to extend R's capabilities. You'll learn how to create visualizations to represent your data clearly and effectively, using various plotting techniques. We'll also introduce linear regression, a fundamental statistical method for modeling relationships between variables.Distributions, Graphics & Neural NetworksIn this Chapter, we will delve into the statistical distributions available in R and how to work with them effectively. You'll also learn to create sophisticated graphics using R's powerful visualization tools. Additionally, we will introduce neural networks, providing a foundation in this advanced machine learning technique.
