Certificate in Time Series Analysis Essentials
-- ViewingNowThe Certificate in Time Series Analysis Essentials is a comprehensive course that equips learners with the essential skills needed to analyze and forecast time series data accurately. This course is vital in today's data-driven world, where businesses rely heavily on time series data to make informed decisions.
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โข Introduction to Time Series Analysis: Defining time series, understanding the components, and the importance of time series analysis.
โข Data Exploration and Preprocessing: Data cleaning, transformations, and visualization for time series data.
โข Decomposition Models: Additive and multiplicative decomposition models, seasonality, and trends.
โข Autoregressive (AR) Models: Defining AR models, stationarity, and identifying AR orders.
โข Moving Average (MA) Models: Understanding MA models, invertibility, and identifying MA orders.
โข Autoregressive Integrated Moving Average (ARIMA) Models: Combining AR, I (difference), and MA models, differencing, and selecting optimal ARIMA parameters.
โข Seasonal ARIMA (SARIMA) Models: Extending ARIMA models for seasonal data, seasonal differences, and selecting optimal SARIMA parameters.
โข Model Evaluation and Selection: Evaluating model fit, residual analysis, information criteria, and model selection.
โข Forecasting with Time Series Models: Creating and interpreting forecasts, prediction intervals, and evaluating forecast accuracy.
โข Exponential Smoothing Models: Simple and Holt-Winters exponential smoothing methods, and selecting optimal smoothing parameters.
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