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|Introduction to time series data||Understanding the basics of time series data, including its characteristics and properties.|
|Exploratory data analysis||Analyzing and visualizing time series data to identify patterns, trends, and anomalies.|
|Detrending and filtering||Removing trends and applying filters to time series data to isolate the underlying patterns.|
|Modeling time series||Building statistical models to capture the underlying structure and behavior of time series data.|
|Forecasting||Predicting future values or trends of a time series based on historical data and model analysis.|
|Applications of time series||Exploring real-world applications of time series analysis, such as demand forecasting and sales predictions.|
|Nonlinear time series analysis||Examining time series data that exhibit nonlinear behavior and applying specialized analysis techniques.|
|Multivariate time series analysis||Analyzing time series data with multiple variables or factors influencing the observations.|
|Chaos theory||Studying the behavior of complex and chaotic time series using mathematical models and algorithms.|
|Financial time series analysis||Applying time series analysis techniques to financial data for forecasting and risk assessment.|