Demand Forecasting Using Time Series

Coursera MOOC / Non-credit USD 49

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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.

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

Skills you'll gain

python demand forecasting arima stationarity autoregressive models trend analysis supply chain time series seasonality correlation methods

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