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所在平台: Udemy |
课程主页: https://www.udemy.com/course/time-series-analysis-in-python/
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课程名称：Python中的时间序列分析 课程概述：如何预测商业银行贷款组合的预期表现？投资经理如何评估股票组合的风险？又有什么定量方法可以用于房地产的预测？如果存在时间依赖性，答案便是时间序列分析。本课程将教授您成为定量金融分析师、数据分析师或数据科学家所需的实用技能。您将迅速掌握在实践中直接适用的复杂时间序列分析基础技能。 我们创建的时间序列课程具有以下特点： - 易于理解 - 内容全面 - 实用性强 - 简明扼要 - 内容丰富，包含大量练习和资源 课程将使用当前最受欢迎的编程语言Python，结合最重要的工具进行实施。我们将从基础理论入手，逐步深入，掌握多个Python库的使用，包括pandas、NumPy、matplotlib、StatsModels、yfinance、ARCH和pmdarima等，利用这些工具掌握最广泛使用的模型，如： - 自回归模型(AR) - 移动平均模型(MA) - 自回归移动平均模型(ARMA) - 自回归积分移动平均模型(ARIMA) - 带外生变量的自回归积分移动平均模型(ARIMAX) - 季节性自回归移动平均模型(SARMA) - 带外生变量的季节性自回归积分移动平均模型(SARIMAX) - 自回归条件异方差模型(ARCH) - 广义自回归条件异方差模型(GARCH) - 向量自回归移动平均模型(VARMA) 课程还提供了大量附加材料，包括笔记本文件、课程笔记、测验问题和练习，确保您全面理解时间序列分析。不仅如此，您还将获得： - 积极的问答支持 - 补充材料 - 从事时间序列分析所需的全部知识 - 数据科学爱好者社区 - 完成课程证书 - 未来更新的访问权限 - 解决实际商业案例的能力，助您就业 我们还提供30天无理由退款保障，风险全无。课程内容卓越，您一定会喜欢。不要犹豫，每天都是错失的机会。点击“立即购买”按钮，开始掌握Python中的时间序列分析吧！
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