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Short Course

Intelligent Process Automation

Course ScheduleDuration (days)Mode of DeliveryTGS Reference Number
To be advised2Classroom LearningTGS-2025057498
To be advised2Synchronous e-LearningTGS-2025057497
This course is offered biannually, available once every six months.

Course Overview

Intelligent Process Automation (IPA) is an emerging set of new technologies that combines robotic process automation, process intelligence and machine learning. It comprises a suite of business process improvements and next-generation tools that aim to eliminate repetitive, replicable, and routine tasks. IPA mimics activities carried out by humans and, over time, learns to do them even better. By leveraging on rules-based automation complemented by deep learning and cognitive technology, IPA aims to enhance worker efficiency, reduce operational risks, and improve customer experiences.

The programme builds upon previous training that participants have undergone in Robotic Process Automation (RPA), to look at how we might integrate Artificial Intelligence (AI), process intelligence capabilities, and Application Programming Interface (API) connectors to expand upon the capabilities of RPA.

Course Objectives

At the end of the course, participants will be able to:

  • Utilise IPA natural language processing and computer vision capabilities.
  • Apply process and task mining to identify process and task inefficiencies, propose improvements and automate them.
  • Employ API connectors to enable automation across different software applications.

Who Should Attend

Professionals, Managers, Executives and Technicians (PMETs).

Prerequisites

Participants with prior experience in Robotics Process Automation.

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This programme is part of

  • Professional Certificate in Robotic Process Automation

    • Types of Available Fundings

  • Enhanced Training Support
  • SFEC
  • PSEA

    • Instructors


    Dr Edmund Low

    Dr Edmund Low

    Dr Edmund Low is currently Senior Lecturer with the NUS College at the National University of Singapore. He has nearly 20 years of academic and professional experience in the use of data-driven tools to answer questions in public health and the environment. His past projects include applying AI techniques and machine learning models for environmental modelling and impact assessment. He currently heads the quantitative reasoning domain at USP, and teaches courses on statistical methods, data science and machine learning. As an educator, Edmund is a multiple recipient of both the USP Teaching Excellence Award, as well as the NUS Annual Teaching Excellence Award. Edmund holds a PhD in Environmental Engineering from Yale University.

    Course Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old
    or younger    		 40 years old
    or older
    Full Course Fee S$2,100.00 S$2,100.00 S$2,100.00 S$2,100.00 S$2,100.00
    9% GST on Full Course Fee S$189.00 S$189.00 S$189.00 S$189.00 S$189.00
    SSG Funding S$1,050.00 S$1,050.00 S$1,050.00 S$1,050.00 -
    Additional Funding if Eligible under Various Schemes - S$420.00 - S$420.00 -
    Total Nett Course Fee Payable, including GST S$1,239.00 S$819.00 S$1,239.00 S$819.00 S$2,289.00
    1. Total nett course fee payable, including GST, after additional funding from various funding schemes.
    2. Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
    3. The applicable funding is for Singaporeans and Singapore PRs. This is subject to change and in accordance with SSG funding guidelines as of course commencement.