NUS
 
ISS
 
NUS ISS

Machine Reasoning

Overview

Reference No TGS-2023021440
Part of Graduate Certificate in Intelligent Reasoning Systems
Duration 4 days
Course Time 9.00AM - 5.30PM
Enquiry Please email ask-iss@nus.edu.sg for more details

Are you harnessing the full potential of intelligent decision-making systems to drive innovation in your business?

In today's competitive landscape, leveraging advanced reasoning systems is essential for businesses aiming to optimise operations and make informed decisions. Machine reasoning offers a sophisticated approach to mimicking human thought processes, enabling machines to reason, learn, and act autonomously. This course provides you with the knowledge and skills to design and implement reasoning systems that can handle complex problems and enhance decision-making capabilities. By integrating logical inference and knowledge representation with big data and machine learning, new opportunities for innovation and strategic growth can be uncovered.

Upcoming Classes

Class 1: 11 January to 15 February 2025 - Class Full
Duration: 4 Days
When: 11, 18 Jan, 1, 15 Feb 2025
Time: 9:00am to 5:30pm

Class 2: 13 to 17 October 2025
Duration: 4 Days
When: 13, 14, 16, 17 Oct 2025
Time: 9:00am to 5:30pm

Register

 

Registration Instructions

Self-sponsored Participants

  • Register for the course by clicking on the "Register Now" button above
  • You may refer to the User Guide for Learner

Company-sponsored Participants

  • You will have to be registered for the course by someone from your company who has an account on the LifeLong Learning Portal (L³AP)
  • The person in-charge may register you for the course by:
    • Generating a corporate registration link for you to register for the course
      • After the link is generated, you must:
        1. Log in to L³AP by clicking on the "Register Now" button
        2. Click on the corporate registration link after logging in
      • If you do not follow the above instructions, you will be registered for the course as self-sponsored
    • Registering you for the course backend
      • You will still be required to log in to L³AP and complete your registration by clicking on the "Register Now" button above
  • You may refer your HR/L&D POC to the User Guide for Company

Course Content

  • Introduction to Reasoning Systems: Understand the evolution from human to machine intelligence and the fundamentals of AI applications in reasoning.
  • Architectures of Reasoning Systems: Explore the structures and cognitive functions of reasoning systems, including learning, perceiving, and acting.
  • Knowledge Representation Techniques: Learn essential techniques for representing and acquiring knowledge, building, and utilising knowledge bases.
  • Deductive Reasoning and Logical Inference: Develop proficiency in deductive reasoning and logical inference, constructing and applying logical models.
  • Reasoning Under Uncertainty: Study methods for handling uncertainty, including probabilistic reasoning and decision-making under various conditions.
  • Contemporary Reasoning Systems: Master the use of modern reasoning systems that integrate big data and machine learning for knowledge discovery and problem-solving.

You will gain practical experience through scenario-based case studies and hands-on sessions using popular tools and frameworks.

This course is a part of the Artificial Intelligence and Graduate Certificate in Intelligent Reasoning Systems, which is a part of the Stackable Graduate Certificate Programme in Artificial Intelligent Systems offered by NUS-ISS.


Key Takeaways

  • Comprehensive Understanding of Machine Reasoning: Grasp the evolution of machine reasoning, its applications, and the architecture of reasoning systems.
  • Knowledge Representation: Learn techniques for representing and acquiring knowledge, essential for enabling machine reasoning.
  • Deductive and Inductive Reasoning: Develop skills in deductive reasoning and logical inference, constructing and applying logical models to solve complex problems.
  • Handling Uncertainty: Understand methods for reasoning under uncertainty, including probabilistic reasoning and decision-making under various conditions.
  • Integration with Big Data and Machine Learning: Discover how contemporary reasoning systems leverage big data and machine learning for knowledge discovery and problem-solving.


    Who Should Attend

    • IT Professionals, Data Scientists, AI Enthusiasts: Enhance your AI skills by incorporating advanced machine reasoning into your toolkit.
    • Professionals Handling Complex Decision-Making: Business and IT professionals seeking to elevate their analytical skills to design and implement reasoning systems that handle complex decision-making processes for optimising operations and strategic planning.
    • Anyone Interested in Intelligent Systems: Anyone interested in developing intelligent systems capable of reasoning, learning, and acting autonomously to solve complex problems and innovate solutions in various domains. 


    Prerequisites

    • Competent in Python programming.
    • Experienced in using Jupyter Notebooks, Google Colab, and well-versed in package installation.


    Course Logistics

    • No Printed Materials: Course materials are accessed digitally. Do kindly note that no printed copies of course materials will be issued.
    • Device Requirements: Bring an internet-enabled device (laptop, tablet, etc) with power chargers to access and download course materials.
    If you are bringing a laptop, kindly refer to the table below for the recommended tech specs:

     

     

    Minimum

    Recommended

    Operating Systems

    • Windows7 and above
    • Mac OS

    Laptop running the latest
    version of either Windows or
    Mac OS

    System Type

    32-bit

    64-bit

    Memory

    8 GB RAM

    16+ GB RAM

    Hard Drive

    256 GB disk size

     

    Others

    		 • An internet connection – broadband wired or wireless
    • Installation permissions (non-company laptops)
    • Keyboard
    • Mouse/Trackpad
    • Display
    • Power adapter (laptop battery might run out)

    DirectX 10 graphics card for graphics hardware acceleration

     
     


    Fees and Subsidies

    SkillsFuture Singapore (SSG) Funding 2024
      Full Course Fees Singapore Citizens & PRs aged 21 years and above 
    (70% funding support)    		 Singapore Citizens aged 40 years and above 
    (90% funding support)    		 Enhanced Training Support for SMEs (ETSS) 
    (90% funding support)
    Full course fee  S$3800 S$3800 S$3800 S$3800
    SSG Funding  - S$2660 S$2660 S$2660
    Nett course fee  S$3800 S$1140 S$1140 S$1140
    9% GST on nett course fee S$342 S$102.60 S$102.60 S$102.60
    Additional Funding if eligible under various schemes  - - S$760 S$760
    Total nett course fee payable, including GST  S$4142 S$1242.60 S$482.60 S$482.60

    Note:
    1. SSG Funding is available to qualified individuals, subject to meeting the attendance requirement and passing of assessment.
    2. All self-sponsored Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees. For more information about SkillsFuture Credit, click here.
    3. SME fees are applicable only to participants who are sponsored by small and medium enterprises.
    4. SSG Funding is valid up to 30 Sep 2024.



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    Certificate

    Certificate of Completion
    Participants have to meet a minimum attendance rate of 75% and are required to pass the assessment to be issued a Certificate of Completion.


    Join Us

    Register now to harness the full potential of intelligent decision-making systems and drive innovation in your organisation.



    Preparing for Your Course

    NUS-ISS Course Registration Terms and Conditions

    Find out more.

    NUS-ISS and Learner’s Commitment and Responsibilities

    Find out more.

    WIFI Access

    WIFI access will be made available to participants.

    Venue

    NUS-ISS
    25 Heng Mui Keng Terrace
    Singapore 119615

    Click HERE for directions to NUS-ISS

    In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.

    Course Confirmation

    All classes are subject to confirmation and NUS-ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by NUS-ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.

    General Enquiry

    Please feel free to write to ask-iss@nus.edu.sg if you have any enquiry or feedback.



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