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Short Course

Data Technology and Management for IT Professionals

Course ScheduleDuration (days)Mode of DeliveryTGS Reference Number
To be advised 2Classroom LearningTGS-2025056821

Course Overview

This introductory course has been developed to introduce modern data management technologies to participants. Among the topics to be analysed are the definition of basic data management techniques and technologies, the background of such technologies, and the future trends of Data Technology and Management (DTM).

This course will also explain the differences between various Data Management approaches, environments, and tools, as well as the advantages and disadvantages associated with their diverse applications. Emerging trends in the field of DTM will be reviewed as well.

Course Objectives

At the end of the course, participants will be able to:

• Understand the basic terms of Data Technology and Management (DTM), along with the characteristics and applications of different applicable DTM techniques
• Articulate the future trends of DTM
• Compare the advantages and disadvantages of the new DTM platforms and tools in different applications
• Recommend a set of tools for a given problem

Who Should Attend

IT engineers, managers, executives and consultants.

Prerequisites

Minimum two years of working experience in the field of IT

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Types of Available Fundings

  • 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.

    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.

    Other Information

    For Singapore Public Service officers, please refer to GovTech Digital Academy webpage for the scheduled class dates and information to register for the course.

    NUS Computing, Advanced Computing for Executives (ACE)

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

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