Time Series Analysis is a specific method of examining a sequence of collected data points over an interval of time. Time Series in R is used to observe how an object behaves over a certain period of time. Analysts record this data at consistent intervals to get accurate data points for the analysis. Time Series forecasting helps in predicting future values based on previously observed values.

This free course starts by explaining the base of Time Series forecasting. You will the various approaches utilized for Time Series forecasting. You will then get introduced to the Decomposition method and how it is used. You will learn about the irregularity concept in the decomposition method. To enhance your learning and understanding of the decomposition method, you will go through a case study on the decomposition method. You will then briefly understand the model forecast theory. Apart from all these theory concepts, you will also get the opportunity to enhance your experience in these concepts through hands-on sessions. You will go through a model forecast hands-on session in R and understand how it works. Next, you will have a hands-on exercise on Time Series forecasting in R. You will also get exposure to exponential smoothing function in R through a hands-on exercise on it. Enroll in this intermediate-level free Time Series Analysis in R course and understand all its concepts with a better approach. Earn a free certification in Time Series Analysis in R on completing the course.

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