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Short Course

Applied Artificial Intelligence

Course ScheduleDuration (days)Mode of DeliveryTGS Reference Number
To be advised2Classroom LearningTGS-2025056131

Course Overview

One of today’s most important technologies that impacts every business from education to healthcare to finance to management is Artificial Intelligence (AI). AI can also help to boost one’s job and career prospects, as one will be able to apply it for problem-solve and enhancing productivity.

This course aims to equip participants with the knowledge and skills to use AI techniques to solve real-world problems. It focuses on two important AI subdomains, logic and search. Logic helps us to develop rules-based expert systems and in this course, we will focus on Fuzzy Logic and train participants on how to design and implement fuzzy rules-based expert systems. Search helps us to solve complicated optimisation problems and in this course, we will focus on evolutionary algorithms, which are one of the most advanced and capable optimisation algorithms. Participants will be taught how to design and develop evolutionary algorithms to solve optimisation problems.

Course Objectives

At the end of this course, participants will be able to:
• Extract logic rules for different problems
• Design and implement basic rules-based fuzzy expert systems
• Design and implement basic evolutionary algorithms
• Solve typical optimisation problems using evolutionary algorithms

Job Role Readiness

Business and market analysts, as well as IT technicians.

Prerequisites

Basic AI knowledge and basic programming skills

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This programme is part of

  • Professional Certificate in AI and Machine Learning Basics

    • Funding Available

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

    • Instructors


    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.

    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$1,900.00 S$1,900.00 S$1,900.00 S$1,900.00 S$1,900.00
    9% GST on Full Course Fee S$171.00 S$171.00 S$171.00 S$171.00 S$171.00
    SSG Funding S$950.00 S$950.00 S$950.00 S$950.00 -
    Additional Funding if Eligible under Various Schemes - S$380.00 - S$380.00 -
    Total Nett Course Fee Payable, including GST S$1,121.00 S$741.00 S$1,121.00 S$741.00 S$2,071.00
    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.
    4. For more information on class cancellations and refunds, please visit our Terms and Conditions page.