Analytics in Industry 4.0 (Synchronous e learning)

TGS-2020502793

Faculty of Science (FOS)

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Objectives

This course is designed to equip participants with the basic knowledge of analytics technologies behind the digital intelligence and pervasive computing extending from factories all the way to homes and offices in order to leverage the power of Industry 4.0 and the Smart Economy. The course will use actual use cases to cover the following:
  • Servitization, Circular Economy, Additive Manufacturing and other drivers and enablers shaping Industry 4.0 and the Smart Economy – Use Case of Managed Services
  • Smart factories and the transformations wrought by Internet of Thing (IoT) and Industrial Internet of Things (IIoT) – Use Case of Production Constraint Diagnosis
  • Big Data, Cloud Computing and the Predictive and Prescriptive Analytics needed for data-driven smart decisions and process automation – Use Case of Demand and Stock Planning
  • Human-machine collaborative efforts, Augmented Intelligence and the future of work and skills needed in Industry 4.0 / Smart Economy – Use Case of Smart Retail Implementation
At the end of the course, participants will be able to:
  • Recognise the characteristics of advanced analytics which makes them key to Industry 4.0
  • Understand the basic underlying concepts of diagnostic analytics in the analysis of factory constraints
  • Understand how predictive analytics techniques such as count data regression could be used to forecast demand
  • Apply basic prescriptive analytics to recommend stocking level of several products sharing WIP space
  • Understand how smart systems should be designed to work with humans responsible for business outcomes



Who Should Attend

This course is designed for business owners, Managers and Professionals who desires to acquire basic understanding of how advanced analytics is shaping Industry 4.0 and how they can be harnessed for their work.




Entry Requirements

Nil




Class Schedule

Please click here



Tutorial Schedule

Same Day as Lecture




Lesson Delivery

a) e-Learning: 13 hours b) Assessment: 1 hour




Full Fees (before GST)

S$1700.00




Nett Fees payable after Funding



International Participant Singapore Citizen 39 years old or younger Singapore Citizen 40 years or older eligible for MCES Singaporean PRs Enhanced Training Support for SMEs
Full Programme Fee S$1700.00 S$1700.00 S$1700.00 S$1700.00 S$1700.00
SSG Funding *
Eligible for Claim Period 1 Jul 2021 to 30 June 2024
- S$1190.00 S$1190.00 S$1190.00 S$1190.00
Nett Programme Fee S$1700.00 S$510.00 S$510.00 S$510.00 S$510.00
8% GST on Nett Programme Fee S$136.00 S$40.80 S$40.80 S$40.80 S$40.80
Total Nett Programme Fee Payable, Incl. GST S$1836.00 S$550.80 S$550.80 S$550.80 S$550.80
Less Additional Funding if Eligible Under Various Scheme - - S$340.00 - S$340.00
Total Nett Programme Fee, Incl. GST, after additional funding from the various funding schemes S$1836.00 S$550.80 S$210.80 S$550.80 S$210.80
*   Learners must fulfill at least 75% attendance and pass all assessment components, to be eligible for SSG funding.

** Please note that the mode of delivery is subject to change in light of the COVID-19 situation. Courses marked ‘online’ may have compulsory face-to-face sessions such as laboratory or hands-on components and details should be sought from the schools or departments before learners register for them.

Upcoming Course Dates
04/05/2023

Delivery Mode**
Online

Course Code
FOS-AII4.0

Funding Type
SSG Funding
Alumni eVoucher (L3)
Alumni eVoucher (R&G)

Type
Short Course

Stacks/ Bundles to
NA

Audit/Graded

Area of Interest
Data Analytics