Expert Systems

Dates: To be advised

Duration: 2 Days

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.

This course is part of Professional Certificate in Artificial Intelligence for Business.

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

    Course Conveners

    (Click their photos to view their short biographies)

    ddddd Akshay Narayan

    Dr Akshay NarayanDr Akshay Narayan

    ddddd Amirhassan Monajemi

    Dr Amirhassan MonajemiDr Amirhassan Monajemi

    Course Fees

    Singapore Citizens
    39 years old or younger
    40 years old or older
    Singapore PRs
    Enhanced Training Support for SMEs
    International Participants

    Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes

    Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.

    To enquire, email soc-ace@nus.edu.sg

    To register, click Register

    Course Codes
    TGS-2022012351 (Classroom Learning)
    TGS-2022012352 (Synchronous e-learning)

    Course Fee Breakdown

     

    Singapore Citizens

    Singapore Citizens

    39 years old or younger

    Singapore Citizen

    40 years old or older
    Singapore PRs
    Enhanced Training Support for SMEs
    International Participants

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