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所在平台: Udemy |
课程主页: https://www.udemy.com/course/r-programming-ninja-course-2021-with-5-real-world-projects/
课程评论：没有评论
课程名称：R编程精英课程2025：数据科学与5个项目 课程概述：数据科学和分析是一个极具回报的职业，能够帮助您解决一些世界上最有趣的问题。在过去的二十年里，数据科学领域迅猛发展，且没有停止的迹象。许多大大小小的企业希望通过大数据获得洞察力。由于其开源特性和极大的灵活性，R已成为统计分析和数据科学的主要工具。面对全球数据科学家短缺的现状，初学者和专业的R程序员都可以进入这个领域。R社区代表了数据科学领域的前沿。 本课程旨在为您提供开始旅程所需的所有知识，使您不必在其他地方回溯学习相关主题。这门课程是您职业生涯起步的终极目的地，提供了启动所需的所有知识、技巧和窍门。课程内容涵盖R的全面知识，重点包括： - R编程语言的概念与重要性：理解统计需求、总体与样本的区别、各种抽样技术。 - 数据类型的核心知识。 - 使用Stringr包进行字符串操作与处理。 - 数据结构（向量、矩阵、数组、列表）。 - 循环、条件和函数，使您在R中具备编程技能。 - 数据框的详细解释及数据分析过程和概念的视角。 - 数据变换的重点介绍，使您熟悉如何处理和转化数据以进行分析。 - 日期时间模块帮助理解并处理R中的日期和时间。 - 描述统计学允许您探索统计数据摘要。 - 使用GGPLOT2进行数据可视化，包括简单和复杂的视觉分析。 所有模块都包括练习题和案例研究，让您了解现实世界的问题，并增强解决问题的能力。5个项目为您提供在数据集上进行分析的机会，鼓励您进一步探索和提升技能，同时增强信心。
Data Science and Analytics is a highly rewarding career that allows you to solve some of the world's most interesting problems. The field of data science has exploded in the past two decades and shows no signs of stopping any time soon. Many big or small businesses and companies wish to make use of the insights gained through the big data.Due to its open-source nature and its extreme versatility, R has become the primary tool for statistical analysis and data science. With the industry facing a shortage of data scientists all over the world, both novice and professional R programmers can enter. R community represents the cutting-edge in the field of data science.This course is made to give you all the required knowledge at the beginning of your journey, so that you don't have to go back and look at the topics again at any other place. This course is the ultimate destination with all the knowledge, tips and trick you would require to start your career.This course provides Full-fledged knowledge of R, we cover it all.Our exotic journey will include the concepts of:What's and Why's of R programming Language - Understanding the need for Statistics, difference between Population and Samples, various Sampling Techniques.Core knowledge for DataTypes.String Manipulation and handling using Stringr PackageData Structures (Vectors, Matrices, Arrays, List)Loops and Conditions and Functions for programming skills in R.Dataframes explained in detail and perspective for Data Analysis Process and Concepts.Most importantly Data Transformations have been covered to make you comfortable with how data should be handled and transformed for analysis.Date Time Module helps to understand and handle date and time in R.Descriptive Statistics allows to explore the data summaries for statistics.Data Visualization using GGPLOT2 used for simple and complex visual analysis.All the modules include practice questions and case studies to give you idea on the real world problems and enhancing problem solving skills.5 Projects allow you to perform analysis on datasets with scope for further exploring and enhancing skills while building confidence.
