Time-Series Analysis comprises methods for analyzing data on time-series to extract meaningful statistics and other relevant information. Time-Series forecasting is used to predict future values based on previously observed values. You will learn several methods such as decomposition, irregularity concept, end-to-end case study for de-composition method to get a realistic overview of how things work in the industry. Understand the basics of Model Forecast Theory and its real-life application.
Skills covered
Time series analysis- Model forecast theory
Course Syllabus
Time Series Analysis in R
Base of time series forecasting- Approaches used for time series forecasting
- Decomposition method
- Irregularity concept in decomposition method
- Case study on decomposition method
- Model forecast theory
- Model forecast hands-on
- Hands-on exercise on time series forecasting
- Hands-on exercise using exponential smoothing function