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Short Course

Blockchain, Internet-Of-Things, and Ubiquitous AI for Metaverse

Programme ScheduleDuration (days)Mode of DeliveryProgramme Code
For Corporate Requests Only2Classroom LearningTGS-2022017238
For Corporate Requests Only2Synchronous e-LearningTGS-2022017239

Course Overview

During this course, participants will be introduced to the applications of Blockchain, Internet of Things (IoT), and ubiquitous Artificial Intelligence (AI) in the Metaverse. The metaverse is a very new technology. It is attempting to give more role to the virtual world. As the origin of the Metaverse is Information and Communications Technology (ICT), its fusion with other modern disruptive ICT technologies may be a considerable advantage for the Metaverse community. We are going to show students how Ubiquitous AI, Blockchain, and IoT can be employed in the Metaverse. The applications, tools, and methodologies will be described and practical aspects would be devised too.

Course Objectives

The metaverse is a new topic. Therefore, executives and experts who know enough about the Metaverse and how to handle that currently are scarce. Any Metaverse skill would be welcomed by the job market at least for a decade. The ICT industry, business, and service sectors, all need Metaverse experts, in particular, experts who know how to gain from other disruptive technologies (e.g. AI, IoT, and Blockchain) in the metaverse. Upon completion of this course, participants would be able to:

  • Articulate the applications of ubiquitous AI (UbAI), IoT, and Blockchain in the Metaverse
  • Realise the merits of applying disruptive technologies in the Metaverse
  • Recognise roadmaps of implementation of disruptive technologies (Blockchain, IoT, UbAI) in the Metaverse.

Prerequisites

  • Diploma holder
  • Basic ICT knowledge
  • Basic Metaverse knowledge
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This programme is part of

  • Professional Certificate in Infrastructure of the Metaverse

    • Types of Available Fundings

  • SkillsFuture Funding
  • SkillsFuture Credit
  • Enhanced Training Support
  • 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.

    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$1,900.00 S$1,900.00 S$1,900.00 S$1,900.00 S$1,900.00
    Less: SSG Grant Amount S$1,330.00 S$1,330.00 S$1,330.00 S$1,330.00 -
    Nett Programme Fee S$570.00 S$570.00 S$570.00 S$570.00 S$1,900.00
    9% GST on Nett Programme Fee S$51.30 S$51.30 S$51.30 S$51.30 S$171.00
    Total Nett Programme Fee Payable, Including GST S$621.30 S$621.30 S$621.30 S$621.30 S$2,071.00
    Less Additional Funding - S$380.00 - S$380.00 -
    Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes S$621.30 S$241.30 S$621.30 S$241.30 S$2,071.00
    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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