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Short Course

Expert Systems

Programme ScheduleDuration (days)Mode of DeliveryProgramme Code
To be advised2Classroom LearningTGS-2022012351

Course Overview

Expert systems (ES) attempt to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural code. A decision support system (DSS) is an information system that supports business or organisational decision-making activities. DSSs serve the management, operations and planning levels of an organization, consequently help people make decisions about complex cases, for example in dealing with unstructured and semi-structured decision problems. Decision support systems can be either fully computerized or human-powered, or a combination of both. In many use cases, DSSs can help businesses. From health management systems, to finance sector, and urban planning, expert systems and DSSs provide diagnostic, decision making, and reasoning services. In this course, we are going to address fundamentals, theory, and practice of expert systems and DSSs.

Course Objectives

The course is devoted to introduce expert systems and decision support systems; show their relationship to different applications in different businesses, and how to design and develop them. Learners will be able to articulate ES and DSS design, implementation approaches and tools.

Who Should Attend

AI experts, AI advisors and AI managers

Prerequisites

Basic AI and ML knowledge

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This programme is part of

  • Professional Certificate in Artificial Intelligence for Business

    • Types of Available Fundings

  • SkillsFuture Funding
  • SkillsFuture Credit
  • Enhanced Training Support
  • SFEC
  • UTAP
  • PSEA

    • Instructors


    Dr Prasanna Karthik Vairam

    Dr Prasanna Karthik Vairam

    Dr Prasanna Karthik Vairam is a faculty member at National University of Singapore. His research areas include software engineering, security and privacy of Internet users, and AI Privacy. He has a Ph.D. in computer science from the Indian Institute of Technology, Madras (IIT Madras) and a M.Tech degree in computer science from the Indian Institute of Technology, Bombay (IIT Bombay). In the past, he was a part of Intel’s processor development team, involved in graphics processor design. At NUS, Prasanna was awarded the Faculty Teaching Excellence Award twice, for 2023 and 2024.

    Dr Amirhassan Monajemi

    Dr Amirhassan Monajemi

    Dr Amirhassan Monajemi is a Senior Lecturer in AI and Machine Learning with the School of Computing (SoC) at the National University of Singapore (NUS). Prior to SoC, he was a Senior Lecturer in NUS School of Continuing and Lifelong Education (SCALE) teaching AI and Data Science to adult learners. Before joining NUS, he was with the Faculty of Computer Engineering, University of Isfahan, Iran, where he was serving as a professor of AI, Machine Learning, and Data Science. He was born in Isfahan, Iran. He studied towards BSc and MSc in Computer Engineering at Isfahan University of Technology (IUT), and Shiraz University respectively. He got his PhD in computer engineering, pattern recognition and image processing, from the University of Bristol, Bristol, England, in 2005. His research interests include AI, Machine Learning, Machine Vision, IoT, Data Science, and their applications. He has taught the artificial intelligence courses, including AI, Advanced AI, Expert Systems, Decision Support Systems, Neural Networks, and Cognitive Science since 2005 at both undergraduate and postgraduate levels. He was awarded the best university teacher of the province in 2012. He also has studied Learning Management Systems, E-Learning, and E-Learning for workplaces since 2007. Dr Monajemi has registered a few patents in the fields of AI, Machine Vision, and Signal Processing applications, including an AI and machine vision-based driver drowsiness detection system and a low power consuming spherical robot. He also has published more than a hundred research papers in peer-reviewed, indexed journals and international conferences (IEEE, Elsevier, Springer, and so on), and supervised several Data Science, IoT, and AI industrial projects in various scales, including Isfahan intelligent traffic system delivery and testing, and red light runners detection. He is experienced in different sub-domains of Artificial Intelligence and Machine Learning, from theory to practice, including Deep Learning, Logic, and Optimisation.

    Programme Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old
    or younger    		 40 years old
    or older
    Full Programme Fee S$2,100.00 S$2,100.00 S$2,100.00 S$2,100.00 S$2,100.00
    Less: SSG Grant Amount S$1,470.00 S$1,470.00 S$1,470.00 S$1,470.00 -
    Nett Programme Fee S$630.00 S$630.00 S$630.00 S$630.00 S$2,100.00
    9% GST on Nett Programme Fee S$56.70 S$56.70 S$56.70 S$56.70 S$189.00
    Total Nett Programme Fee Payable, Including GST S$686.70 S$686.70 S$686.70 S$686.70 S$2,289.00
    Less Additional Funding - S$420.00 - S$420.00 -
    Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes S$686.70 S$266.70 S$686.70 S$266.70 S$2,289.00
    1. Total Nett Programme 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. Please note that all external funding for courses is limited in duration and subject to eligibility and availability.

    Other Information

    This course is eligible for Union Training Assistance Programme (UTAP). NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. NTUC members aged 40 and above can enjoy higher funding support up to $500 per individual each year, capped at 50% of unfunded course fees, for courses attended between 1 July 2020 to 31 December 2025. Please click here for more information.

    Advanced Computing for Executives

    11 Research Link
    COM 3, #B1-07
    Singapore 119391
    Email: soc-ace@nus.edu.sg

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