Demand Forecasting Using Time Series
About this Course
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.Created by: LearnQuest
Related Online Courses
This course focuses on data, evaluation methods and the economic evaluation of digital health interventions. This module focuses on key data considerations for digital health including data... more
Growing a business needs a dynamic set of skills, ranging from leadership, employee management, strategy, planning, finance, accounting, ethics, accountability, and profitability.\\n\\nDeveloped at... more
The course will explore the tone combinations that humans consider consonant or dissonant, the scales we use, and the emotions music elicits, all of which provide a rich set of data for exploring... more
This specialization equips learners with in-depth knowledge of Agile principles and Scrum frameworks, focusing on backlog mastery, sprint planning, and continuous improvement. Learners will gain... more
There are numerous types of machine learning algorithms, each of which has certain characteristics that might make it more or less suitable for solving a particular problem. Decision trees and... more
Powered by
