Demand Forecasting Using Time Series
About this course
In this course, you’ll delve into time series analysis specifically for predicting demand, which is crucial for effective supply chain management. You’ll cover essential concepts like stationarity and seasonality, and learn how to apply correlation methods, especially autocorrelation, to time series data. The course culminates in a practical project where you will implement ARIMA models in Python to forecast demand, solidifying your understanding of the subject.
67/100
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- What the provider tells you
- 31/45
- Who stands behind it
- 20/35
- How complete the listing is
- 16/20
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What you'll learn
- understand fundamental concepts of time series analysis
- analyze time series data for demand prediction
- apply autoregressive models for forecasting
- predict demand using ARIMA models in Python
Course objectives
- explore the basic concepts of time series
- analyze correlation methods related to time series
- implement demand forecasting techniques using Python
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