Demand Forecasting Using Time Series
half-circle
vector

Demand Forecasting Using Time Series

Highlights

This course is the second in a specialization for Machine Learning for Supply Chain Fundamentals. In this course, we explore all aspects of time series, especially for demand prediction. We'll start by gaining a foothold in the basic concepts surrounding time series, including stationarity, trend (drift), cyclicality, and seasonality. Then, we'll spend some time analyzing correlation methods in relation to time series (autocorrelation). In the 2nd half of the course, we'll focus on methods for demand prediction using time series, such as autoregressive models. Finally, we'll conclude with a project, predicting demand using ARIMA models in Python.

About the Course Provider

Coursera provides access to more than 3000+ courses across a wide variety of subjects in parntership with different universities and organizations.

Course by

  • self
    Self paced
  • dueration
    Duration 9 hours
  • domain
    Domain Data Science & AI
  • subs
    Monthly Subscription
    Course is included in
    1. Starter @ AED 99 + VAT
    2. Professional @ AED 149 + VAT
  • fee
    Buy Now Option not available
  • language
    Language English