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.
NE
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
Best explanation of the key concepts in short time. Well done.
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you did not post the course files. Even after several post asking for the files. I contacted support and they did not help either.
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).
No datasets provided, makes the course less useful.
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.
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!
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.
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.
Best explanation of the key concepts in short time. Well done.
Excelente curso, lo reomiendo
Thanks!
none
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
missing some extra foundational math details to fully grasp how to use these tools. good course to start.
Too shallow, but good introduction on ARMA Models
Contents were very less.
I expected a lot more.