Optimising the Supply Chain through RPA and Machine Learning

This programme is developed in partnership with SMU Academy. The 5-day practical program provides hands-on skills training in Machine Learning and Robotic Process Automation. 

Every physical product that we have today results from a supply chain execution – a complex series of steps that turn raw materials into the final products we use and everything related to this. 

Managing these supply chains has become more challenging, especially with all modern technologies and today’s trends. The 24-hour economy, fast delivery of goods to your home, wanting to have customised products, and of course, the focus on sustainability are a few of these trends.

In this program, you will learn why managing supply chains are essential and challenging. It is a critical activity in both large multi-national companies as well as for small businesses. We’ll find out how to incorporate technologies into logistics and supply chain operations that are not only effective – but efficient. 

The course will provide foundational knowledge in the following areas:

  • State of global supply chain and logistics development today
  • Impact of digitalisation on supply chain operations
  • Adoption and implementation of tech solutions such as Robotic Process Automation and Machine Learning

In this program, we will also be exploring the successes/challenges relating to the adoption of emerging technologies in the logistics and supply chain sector.

To add practical benefits, all trainees participating in this course will need to complete TWO project work relating to Machine Learning and Robotic Process Automation. These two projects must be submitted on Day 5 as the final requirement for completing the course and awarding the Professional Certificate in Supply Chain Innovation by Singapore Management University (SMU) Academy.

Day 1 – Introduction to Supply Chain Innovation & RPA

  • Introduction to Supply Chain Innovation
  • Overview of Robotic Process Automation
  • RPA System Set-up and Overview 

Day 2 – Robotic process Automation (RPA)

  • RPA Practical Exercises (Build 7 Bots)
  • RPA Automation Challenge

Day 3 – machine learning using python

  • Introduction to Machne Learning
  • Machine Learning and Data Science Framework
  • Data Science Environment Setup
  • Introduction to Pandas, Numpy and Matplotlib

Day 4 – machine learning using Juptyer notebook

  • Scikit-learn: Creating Machine Learing Models
  • Hands-on Milestone Project
  • Introduction Supply Chain Innovation Maturity Matrix
  • Application of Supply Chain Innovation Toolkit

Day 5 – Project presentation/course review

  • Practical Exercise 1 – Development of an RPA Bot
  • Practical Exercise 2 – Development of a Machine Learning Application
  • Project Presentation

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