In today's data-driven world, the ability to accurately forecast and predict future trends is crucial for businesses to stay ahead of the competition. Time series analysis is a powerful tool that allows organizations to unravel patterns and make informed decisions. This course, Time Series Mastery: Unravelling Patterns with ETS, ARIMA, and Advanced Forecasting Techniques, provides a comprehensive introduction to time series analysis and forecasting. You will learn about the most widely used techniques, including Error-Trend-Seasonality (ETS), Autoregressive Integrated Moving Average (ARIMA), and advanced forecasting methods. By the end of this course, you will have the skills and knowledge to apply these techniques to real-world data and make accurate predictions.

Time Series Mastery: Forecasting with ETS, ARIMA, Python
本课程是多个项目的一部分。


位教师:Diogo Resende
访问权限由 New York State Department of Labor 提供
2,789 人已注册
您将学到什么
Apply the most widely used techniques, including Exponential Smoothing (ETS) and Autoregressive Integrated Moving Average (ARIMA).
Analyze real-world data to identify patterns and make accurate predictions.
Create advanced forecasting models using Python.
您将获得的技能
要了解的详细信息

可分享的证书
添加到您的领英档案
作业
4 项作业
授课语言:英语(English)
了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识
此课程作为 的一部分提供
在注册此课程时,您还需要选择一个特定的合作项目。
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书

该课程共有1个模块
获得职业证书
将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。
提供方
人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.
自 2018开始学习的学生
''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情,我就可以学习。'

Jennifer J.
自 2020开始学习的学生
''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

Larry W.
自 2021开始学习的学生
''如果我的大学不提供我需要的主题课程,Coursera 便是最好的去处之一。'

Chaitanya A.
''学习不仅仅是在工作中做的更好:它远不止于此。Coursera 让我无限制地学习。'
学生评论
- 5 stars
56.81%
- 4 stars
13.63%
- 3 stars
11.36%
- 2 stars
11.36%
- 1 star
6.81%
显示 3/44 个
NE
已于 Jun 12, 2024审阅
I think it was too basic, it lacks more a deeper dive into theoretical aspects and importance about the different scores that the summary of the model provides. However it's a good introduction
KK
已于 Oct 16, 2024审阅
Best explanation of the key concepts in short time. Well done.






