Time Series Analysis is a particular method for analyzing the sequence of data points across a period of time. Time Series in R is utilized to study the way an object behaves during a specific period of time. Analysts collect these data in regular intervals to obtain precise data points to analyze. Time Series forecasting helps in forecasting future values based on previous observations of values. This course begins by introducing the fundamentals for Time Series forecasting. Learn about the different approaches used to perform Time Series forecasting. Then, you will be familiar with how to use the Decomposition method and the way it is applied. Learn about the concept of irregularity in the method of decomposition. To increase your knowledge as well as understanding the method of decomposition it is recommended to go through an example study of the method of decomposition. Then, you will be able to briefly comprehend the theory of forecasting models. In addition to all these theoretical concepts, you'll also be able to improve your understanding of these concepts by participating in hands-on workshops. The course will take you through an interactive model forecast session in R and learn the process behind it. Then, you'll be able to do an exercise that is hands-on on Time Series forecasting in R. Additionally, you will get an introduction to the exponential smoothing function in R by doing a hands-on activity on it. Join this intermediate-level, free Time Series Analysis in R course to grasp all of its principles with a more thorough method. Get a certificate of completion for Time Series Analysis in R after completion of the course. Take a take a look at the Best Data Science Courses to learn more about Data Science concepts in-depth. Join our highly regarded degree and PG courses of your choice and receive an award for successful completion of the courses.
