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This lecture covers demand forecasting methods and models, including quantitative and qualitative approaches, causal models, time series analysis, and trend forecasting. It also explores the use of Excel for forecasting and the application of the Holt-Winter model for trend and seasonality. The session delves into autocorrelation analysis, detecting seasonality, and the components of time series data, such as trend and seasonal patterns. Practical exercises are provided to apply the concepts discussed, including forecasting demand using exponential smoothing with trend and the Holt model.