Go to Course: https://www.coursera.org/learn/time-series-mastery-forecasting-with-ets-arima-python
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.
Time Series Mastery: Forecasting with ETS, ARIMA, Python
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 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.
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 tech
Best explanation of the key concepts in short time. Well done.
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