Time series decomposition course,
in this course provides an in-depth understanding of time series decomposition, breaking down data into its fundamental components: trend, seasonal, and irregular variations. You’ll learn to identify patterns, distinguish between additive and multiplicative models, and analyze data for forecasting and decision-making. The course covers seasonal adjustments, trend analysis, and cyclical patterns using real-world examples and practical applications. By mastering these techniques, you'll gain the skills to handle complex time series data effectively and derive actionable insights. Ideal for analysts, researchers, and students, this course is designed to enhance your proficiency in understanding and interpreting time series dynamics.
