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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-visualizations-using-r-with-data-processing/
课程评论：没有评论
R语言数据可视化与数据处理课程概述 本课程是关于使用R语言进行数据可视化和数据处理的入门级课程。课程旨在教授学员如何通过R语言，有效地理解和准备数据，并利用可视化技术展现数据洞察。 **为何学习数据分析与数据科学？** * **提升解决问题的能力：** 培养分析性思维，有效应对工作和生活中的挑战。 * **高需求行业：** 数据分析师和数据科学家是备受追捧的职业，随着各行各业对数据的依赖增加，其价值将持续攀升。 * **应用无处不在：** 数据分析渗透到各个企业和领域，帮助企业从数据中获取有价值的洞察，优化流程。 * **重要性日益凸显：** 随着数据量的爆炸式增长，从数据中发掘见解以支持决策变得前所未有的重要，为数据分析师创造了更多更好的就业机会。 * **技能多元化：** 数据分析领域融合了计算机科学、商业和数学等多个学科，并强调将复杂信息清晰传达给非专业人士的能力。 **课程与R语言编程基础的关联：** 本课程是“创建你的计算器：快速学习R语言基础”课程的进阶。学习R语言编程是掌握数据分析和数据科学的关键。 **学习途径与认证：** 学员可以通过以下系列课程进行学习，并在EMHAcademy参加考试，获得“SVBook认证数据挖掘师（R）”证书： 1. 创建你的计算器：快速学习R语言基础 (R Basics) 2. R语言应用统计与数据处理 (Data Understanding and Data Preparation) 3. （未来）R语言高级数据可视化与数据处理 (Data Understanding and Data Preparation) 4. R语言机器学习 (Modeling and Evaluation) **课程内容涵盖：** * **入门：** R语言入门、Hello World应用、数据挖掘流程介绍。 * **数据导入：** 下载和读取数据集。 * **基础图表可视化：** * 条形图（柱状图）及导出为图片 * 水平条形图 * 直方图（含密度线） * 折线图（含多条折线图） * 饼图（含3D饼图） * 散点图 * 箱线图 * 散点图矩阵 * **GGPlot2可视化：** * 基本概念：美学映射 (Aesthetic Mapping) 和几何对象 (Geometrics) * 图表元素：标签和标题 * 图表主题 (Themes) * 使用GGPlot2绘制：条形图、直方图、密度图、散点图、折线图、箱线图 * 保存GGPlot2图表为图片 * **数据处理：** * 变量选择 * 数据排序 * 数据过滤 * 去除重复值与缺失值 **课程资源：** 本课程内容基于作者出版的Apress书籍“Learn R for Applied Statistics”。
Why learn Data Analysis and Data Science?According to SAS, the five reasons are1. Gain problem solving skillsThe ability to think analytically and approach problems in the right way is a skill that is very useful in the professional world and everyday life. 2. High demandData Analysts and Data Scientists are valuable. With a looming skill shortage as more and more businesses and sectors work on data, the value is going to increase. 3. Analytics is everywhereData is everywhere. All company has data and need to get insights from the data. Many organizations want to capitalize on data to improve their processes. It's a hugely exciting time to start a career in analytics.4. It's only becoming more importantWith the abundance of data available for all of us today, the opportunity to find and get insights from data for companies to make decisions has never been greater. The value of data analysts will go up, creating even better job opportunities. 5. A range of related skillsThe great thing about being an analyst is that the field encompasses many fields such as computer science, business, and maths. Data analysts and Data Scientists also need to know how to communicate complex information to those without expertise.The Internet of Things is Data Science + Engineering. By learning data science, you can also go into the Internet of Things and Smart Cities. This is the bite-size course to learn R Programming for Data visualizations. In CRISP-DM data mining process, Data Visualization is at the Data Understanding stage. This course also covers Data processing, which is at the Data Preparation Stage. You will need to know some R programming, and you can learn R programming from my "Create Your Calculator: Learn R Programming Basics Fast" course. You will learn R Programming for applied statistics and you will be able You can take the course as follows, and you can take an exam at EMHAcademy to get SVBook Certified Data Miner using the R certificate: - Create Your Calculator: Learn R Programming Basics Fast (R Basics)- Applied Statistics using R with Data Processing (Data Understanding and Data Preparation)- Advanced Data Visualizations using R with Data Processing (Data Understanding and Data Preparation, in the future)- Machine Learning with R (Modeling and Evaluation)ContentGetting StartedGetting StartedGetting StartedHello World ApplicationData Mining ProcessDownload DatasetRead DatasetBar PlotExport Bar Chart as ImageHorizontal Bar ChartHistogramHistogram with Density LineLine ChartMultiple Line ChartPie Chart3D Pie ChartScatterplotBoxplotScatterplot MatrixGGPlot 2Aesthetic Mapping and GeometricGEometricsLabels and TitlesThemesGGPlot2: Bar CHartGGPlot2: HIstogramGGPlot2: Density PlotGGPlot2: ScatterplotGGPLot2: Line ChartGGPLot2: BoxpLotSave GGPLot ImageData Processing: Select VariablesData Processing: Sort DataData Processing: Filter DataData Processing: Remove Duplicates and Missing ValuesReferences: This course is actually based on the Learn R for Applied Statistics book I have published at Apress.
