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Short Course

ChatGPT and its Applications

Programme ScheduleDuration (days)Mode of DeliveryProgramme Code
To be advised2Classroom LearningTGS-2025056117
To be advised2Synchronous e-LearningTGS-2025056114

Course Overview

ChatGPT has got a wide range of applications. Also, it is a rather user friendly application. However, the main challenge is when and how to employ it. We are going to show the participants a set of clear hints and practices about the tool, and when and how to use it. Again, this is a way to learn more about the ChatGPT models. This course provides a practical and comprehensive overview of ChatGPT, from subscription to mastering its advanced features. Best practices and hints for using ChatGPT are also included. Also, the ethical issues and the risks concerning ChatGPT would be addressed in this course as well as business robotising using ChatGPT.

Course Objectives

After attending this course, participants will be able to:

  • Understand ChatGPT and its major components
  • Make decisions using ChatGPT
  • Do predictive data analysis using ChatGPT
  • Articulate advanced features and capabilities of ChatGPT
  • Use ChatGPT as an advisor or robot
  • Fine-tune ChatGPT robot for a specific business
  • Understand the strengths, weaknesses, risks and limitations of ChatGPT

Prerequisites

Minimum of a diploma with basic ICT knowledge

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This programme is part of

  • Professional Certificate in ChatGPT, Advanced Chat Models, and Generative AI

    • Types of Available Fundings

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

    • Testimonials


    This is a good course with a right mix of theory and hands-on exercises.

    Very good course to start off your LLM journey.

    Good course to improve AI knowledge.

    Overall satisfying, very insightful sessions.

    Instructor explains very clearly so concepts could be easily understood.

    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.

    Dr Sanka Rasnayaka

    Dr Sanka Rasnayaka

    I am a lecturer at the School of Computing, National University of Singapore.

    My teaching philosophy is to facilitate self-learning by guiding students' thinking towards the final learning outcome, rather than explaining to them how to get there. I enjoy teaching fundamental courses in Computer Science like Discrete Structures, Programming, Algorithms and specialised courses in AI, Machine Learning and Computer Vision.

    My research interests are on Continuous Authentication for modern personal devices, on-body gait biometric, privacy and human perceptions.

    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$1,700.00 S$1,700.00 S$1,700.00 S$1,700.00 S$1,700.00
    9% GST on Full Programme Fee S$153.00 S$153.00 S$153.00 S$153.00 S$153.00
    Less: SSG Grant Amount S$850.00 S$850.00 S$850.00 S$850.00 -
    Nett Programme Fee S$850.00 S$850.00 S$850.00 S$850.00 S$1,700.00
    Total Nett Programme Fee Payable, Including GST S$1,003.00 S$1,003.00 S$1,003.00 S$1,003.00 S$1,853.00
    Less Additional Funding - S$340.00 - S$340.00 -
    Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes S$1,003.00 S$663.00 S$1,003.00 S$663.00 S$1,853.00
    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. 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.

    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.

    NUS Computing, Advanced Computing for Executives (ACE)

    11 Research Link
    COM 3, #B1-07
    Singapore 119391

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