Demand Forecasting Using Time Series

This is the second course in a specialization on Machine Learning for Supply Chain Fundamentals. This course will cover all aspects of time series, including demand prediction. We will start with a basic understanding of time series concepts, such as trend (drift), stationarity, cyclicality and seasonality. We'll then spend time analysing correlation methods in relation time series (autocorrelation). The second half of the course will focus on demand prediction methods using time series such as autoregressive model. We'll end the course with a Python project that predicts demand using ARIMA models.