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所在平台: Udemy |
课程主页: https://www.udemy.com/course/time-series-analysis-for-beginner-from-scratch/
课程评论：没有评论
**课程名称：Python与R时间序列分析** **课程概述：** 本课程旨在教授学员时间序列分析的基础概念、预测技术以及实际应用。时间序列研究的核心目标包括描述、预测、解释和控制。其中，预测未来事件对于市场营销、金融风险管理、经济学、工业过程控制、人口统计学等众多领域的规划和决策至关重要。 课程将重点讲解两种主要的预测方法：定性方法和定量方法。定性方法依赖专家的主观判断，而定量方法则利用历史数据和统计模型，通过识别数据中的模式来预测未来趋势。 **课程内容：** * **时间序列分析的目标：** 深入理解描述、预测、解释和控制在时间序列分析中的重要性。 * **预测的重要性：** 探讨预测在各领域规划与决策中的关键作用。 * **预测方法：** * **定性预测：** 介绍基于专家判断的主观预测技术。 * **定量预测：** 重点学习利用历史数据和统计模型进行预测的方法，包括理解模型如何总结数据模式并建立统计关系。 * **Python与R实战：** 课程将提供丰富的实验环节，学员可以使用Python和R这两种在数据科学领域最常用的语言，将理论知识应用于实际案例。 **学习收获：** 通过本课程的学习，学员将掌握时间序列分析的基本理论和方法，熟悉各类预测技术，并能够利用Python和R进行实际的时间序列数据分析和预测。课程还将提供大量实践实验室，助力学员巩固和提升技能。
There are several reasons why it is desirable to study a time series.In general, we can say that, the study of a time series has as main objectives:DescribePredictExplainControlOne of the most important reasons for studying time series is for the purpose of making forecasts about the analyzed time series.The reason that forecasting is so important is that prediction of future events is critical input into many types of planning and decision-making processes, with application to areas such Marketing, Finance Risk Management, Economics, Industrial Process Control, Demography, and so forth.Despite the wide range of problem situations that require forecasts, there are only two broad types of forecasting techniques. These are Qualitative methods and Quantitative methods.Qualitative forecasting techniques are often subjective in nature and require judgment on the part of experts.Quantitative forecasting techniques make formal use of historical data and a forecasting model. The model formally summarizes patterns in the data and expresses a statistical relationship between previous (Tn-1), and current values (Tn), of the variable.In other words, the forecasting model is used to extrapolate past and current behavior into the future. That's what we'll be learning in this course.Regardless of your objective, this course is oriented to provide you with the basic foundations and knowledge, as well as a practical application, in the study of time series.Students will find valuable resources, in addition to the video lessons, it has a large number of laboratories, which will allow you to apply in a practical way the concepts described in each lecture.The labs are written in two of the most important languages in data science. These are python and r.
