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Introduction to time series dataUnderstanding the basics of time series data, including its characteristics and properties.
Exploratory data analysisAnalyzing and visualizing time series data to identify patterns, trends, and anomalies.
Detrending and filteringRemoving trends and applying filters to time series data to isolate the underlying patterns.
Modeling time seriesBuilding statistical models to capture the underlying structure and behavior of time series data.
ForecastingPredicting future values or trends of a time series based on historical data and model analysis.
Applications of time seriesExploring real-world applications of time series analysis, such as demand forecasting and sales predictions.
Nonlinear time series analysisExamining time series data that exhibit nonlinear behavior and applying specialized analysis techniques.
Multivariate time series analysisAnalyzing time series data with multiple variables or factors influencing the observations. 
Chaos theoryStudying the behavior of complex and chaotic time series using mathematical models and algorithms. 
Financial time series analysisApplying time series analysis techniques to financial data for forecasting and risk assessment.

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