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学生对 Coursera Instructor Network 提供的 Time Series Mastery: Forecasting with ETS, ARIMA, Python 的评价和反馈

4.0
40 个评分

课程概述

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. Targeted at business analysts, data scientists, financial analysts, and market researchers, this course provides essential skills and insights to excel in today's data-driven business environment, equipping learners with the tools to drive strategic decision-making and foster organizational growth....

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1 - Time Series Mastery: Forecasting with ETS, ARIMA, Python 的 15 个评论(共 15 个)

创建者 Javier

Sep 8, 2024

you did not post the course files. Even after several post asking for the files. I contacted support and they did not help either.

创建者 Stefan N

Nov 18, 2024

The word “Mastery” in the title is somewhat misleading. The course only provides an initial overview and introduction to the subject. However, that goal is achieved well. In the course, a Python notebook with a data set is worked through. Although the lecturer announces that both will be provided, this is not the case. Even after repeated requests from various students in the discussion forums, the resources were not provided. If you want to follow the programming examples, you have to get a data set yourself (e.g. on Kaggle).

创建者 John W

Jul 19, 2024

No datasets provided, makes the course less useful.

创建者 Teck H S

Sep 17, 2024

Not worth the time to attend this course. Course title should be "... Brief Overview ,,," instead of "... Mastery..." There were typo-errors in the course slides. Coursera MUST audit the quality of courses introduced into the platform.

创建者 Deleted A

Aug 23, 2024

Not a course but trash! There is no dataset files to the course. Lecturer don't know PEP-8. pmdarima is bad library it calculates to long. Course structure is awful!

创建者 Kanza N

Mar 17, 2025

For anyone new to time series forecasting, this course is a fantastic resource. The explanations are straightforward, the content is well-structured, and the instructor ensures that learners can follow along easily.

创建者 Kiran

Oct 17, 2024

Best explanation of the key concepts in short time. Well done.

创建者 Or K K

Aug 4, 2024

Thanks!

创建者 hassan b

Mar 4, 2025

none

创建者 Nicolás E

Jun 12, 2024

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

创建者 Esteban M

Jul 9, 2024

missing some extra foundational math details to fully grasp how to use these tools. good course to start.

创建者 Harshvardhan K

Jun 8, 2025

Too shallow, but good introduction on ARMA Models

创建者 Gerald R

Jan 30, 2025

This is a general overview of the subject and as such is sufficient. The explanations feel very scripted and stiff. Therefore, the empowerment message in the final video is a severe hyperbole. No exercise data is available to a least trace the presented steps yourself and play around with the tools mentioned. So there are no practical assignments. The whole course is more like a youtube video, but maybe I am spoilt by better coursera courses.

创建者 Yashaswi R

Dec 2, 2024

Contents were very less.

创建者 יובל כ

Oct 13, 2024

I expected a lot more.