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Back to Time Series Mastery: Forecasting with ETS, ARIMA, Python

Learner Reviews & Feedback for Time Series Mastery: Forecasting with ETS, ARIMA, Python by Coursera Instructor Network

3.5
stars
20 ratings

About the Course

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 - 11 of 11 Reviews for Time Series Mastery: Forecasting with ETS, ARIMA, Python

By 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.

By 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).

By John W

Jul 19, 2024

No datasets provided, makes the course less useful.

By 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.

By Alexander K

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!

By Kiran

Oct 17, 2024

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

By Or K K

Aug 4, 2024

Thanks!

By 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

By Esteban M

Jul 9, 2024

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

By Yashaswi R

Dec 2, 2024

Contents were very less.

By יובל כ

Oct 13, 2024

I expected a lot more.