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Supply Chain Analytics in Python

Course Cover

5

(3)

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Supply Chain Analytics can transform supply chain activities from guessing to those who make data-driven decisions. Supply Chain Analytics is a vital tool for optimization analysis. It helps in decision making. According to Deloitte, 79% of companies that have highly-performing supply chains experience revenue growth that is significantly greater than the average. This course will show you how to use PuLP (a Python-based Linear Program Optimizer modeler). This course will show you how to use PuLP for Supply Chain Optimization questions such as where a production facility should be located or how to distribute production demand across multiple facilities. We will analyze the consequences of the models through simulation and sensitivity testing. This course will teach you how to use Python or PuLP to improve supply-chain decision making.

Course Overview

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Virtual Labs

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International Faculty

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Case Based Learning

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Post Course Interactions

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Case Studies,Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Data Manipulation with pandas

What You Will Learn

Leverage the power of Python and PuLP to optimize supply chains

Linear Programming (LP) is a key technique for Supply Chain Optimization

In this chapter we continue to learn how to model LP and IP problems in PuLP

Course Instructors

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Aaren Stubberfield

Manager, Supply Chain Analytics @ Ingredion Incorporated

Manager of Supply Chain Analytics, with over 7 years of experience analyzing data to find insight for business related questions. I am responsible Supply Chain related Analytics for the NA business f...

Course Reviews

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