Capstone Project: Predicting Safety Stock

Overview

Title:

Capstone Project:

Predicting Safety Stock

Description:

Dive into the fascinating world of predictive analytics with our course on Predicting Safety Stock. Focused on the dynamic realm of shoe sales spanning multiple stores across three continents, this course offers participants an in-depth exploration of product usage forecasting and the calculation of optimal safety stock levels.

Beginning with a comprehensive analysis of time-series data, attendees will engage in identifying patterns, insights, and unique distinctions within the data by grouping and comparing product performances across various locations. Leveraging the powerful seasonal autoregressive integrated moving average (SARIMA) model, participants will learn to forecast future sales with a high degree of accuracy.

The course meticulously guides through the evaluation of model viability using statistics like the p-score and fine-tunes the model’s hyper-parameters to achieve superior predictive performance and statistical significance. Culminating with the application of these forecasts to determine monthly safety stock requirements, the course empowers learners to apply these insights, utilizing specific formulas that incorporate lead times.

Offered by Coursera, this course is an invaluable resource for professionals and enthusiasts in the Artificial Intelligence, Data Analysis, pandas, Supply Chain, and Inventory Management sectors, seeking to enhance their predictive analytics capabilities.

University:

Provider:

Coursera

Categories:

Artificial Intelligence Courses, Data Analysis Courses, pandas Courses, Supply Chain Courses, Inventory Management Courses

Taught by

Rajvir Dua and Neelesh Tiruviluamala

Subjects