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所在平台: Udemy |
课程主页: https://www.udemy.com/course/r-for-data-analysts/
课程评论：没有评论
课程名称：R编程数据分析终极指南 课程概述：你想成为一名数据分析师吗？希望获得实用的技能并解决实际业务问题？那么这门课正适合你！本课程由一位在保险和医疗保健行业拥有10年经验的高级数据分析师创建，将为你提供基础知识，帮助你学习数据加载、数据处理、数据聚合以及如何简单使用库/软件包的关键概念。我将逐步引导你进入数据分析的世界。在每次讲座和实验中，你将逐步掌握这些概念，以应对实际数据问题！本课程主要采用R语言进行实验和顶点项目的解决。 课程内容设计得非常合理，逻辑流畅： - 模块0 - R语言简介：设置R环境，了解R包/库的基础知识 - 模块1 - 数据加载与写入：学习如何从平面文件（如.csv或Excel格式）加载和写入数据 - 模块2 - 数据类型与格式化：掌握数据类型，学习如何转换数据类型以进行正确的操作 - 模块3 - 数据处理：清理和预处理数据，进行排序、顺序和记录子集 - 模块4 - 连接操作：学习如何使用R包（如dplyr和sqldf）执行连接操作 - 模块5 - 数据聚合：学习如何使用汇总统计聚合数据，并进行特征工程 - 模块6 - 时间智能：学习如何计算工作日和时间维度分析 - 模块7 - 数据可视化：学习探索性数据分析（EDA）及单变量/双变量可视化的基础知识 每个模块都是独立的内容，技术上，你可以从头到尾完成课程，或跳到你感兴趣的特定主题。然而，我强烈建议学生按照模块1到模块7的顺序进行学习，以完成顶点项目挑战！本课程充满了我在高级数据分析师职业生涯中解决的真实数据/业务问题。你不仅会学习到概念，还会获得很多实践经验。今天就报名吧，迈出掌握使用R进行数据分析艺术的第一步！
Interested in becoming a Data Analyst? Want to gain practical skills and solve real-world business problems? Then this is the perfect course for you! This course is created by a Senior Data Analyst who has 10 years of experience in the Insurance and Health Care sectors. This course will equip you with foundational knowledge and help you learn key concepts of loading data, data manipulation, data aggregation, and how to use libraries/packages in a simple method.I will guide you step-by-step into the World of Data Analysis. With every lecture and lab exercise, you will gain and develop understandings of these concepts to tackle real data problems! This course is mainly designed using R to solve the labs and capstone projects.This course will be super useful and exciting. I tried my best to design the course curriculum in the most natural logical flow:· Module 0 - Intro to R: set up R environment and understand the basics of R packages/libraries· Module 1 - Load and Write Data: learn how to load and write data from flat files (i.e.,.csv or Excel format)· Module 2 - Data Types and Formatting: master the data types and learn how to convert data types for right operations· Module 3 - Data Manipulation: clean and preprocess data, perform sorting, ordering, and subsetting records· Module 4 - Join Operations: learn how to perform joins using R packages (i.e., dplyr and sqldf)· Module 5 - Data Aggregation: learn how to aggregate data using summary statistics and perform feature engineering· Module 6 - Time Intelligence: learn how to calculate business days and time dimension analysis· Module 7 - Data Visualization: learn the basics of exploratory data analysis (EDA) and uni-variate/bi-variate visualizationsEach module is independent content. Technically speaking, you can take the course from start to end or jump into any specific topics of your interest. However, I highly recommend students to take the course from Module 1 to 7 in order to complete the capstone project challenge!This course is packed with real-world data/business problems that I solved during my career as a senior data analyst. You will learn not just concepts but also a lot of practical and hands-on experience from the course. Enroll today and take the first step towards mastering the art of data analysis using R.
