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Professional Certificate

Professional Certificate in AI and Machine Learning Basics

Programme Structure


Programme NameProgramme ScheduleMode of DeliveryProgramme Code
AI and Machine Learning Begins with MeTo be advisedClassroom LearningTGS-2020506039
Octave Programming for AI, Machine Learning and Data AnalyticsTo be advisedClassroom LearningTGS-2020513881
 To be advisedSynchronous e-LearningTGS-2020504956
Applied Artificial IntelligenceTo be advisedClassroom LearningTGS-2020513880
Introduction to RapidminerTo be advisedSynchronous e-LearningTGS-2022012285
 To be advised Classroom LearningTGS-2022012249
Duration 6 days

Programme Overview

This course provides a combination of theory and practice for participants and will articulate the fundamentals of AI and Machine Learning. Participants will also learn how to deploy AI and Machine Learning in real-world business environments.

Programme Objectives

This Professional Certificate will equip learners with the following competencies:

  • Articulating AI and Machine Learning definitions, approaches, and applications.
  • Understanding AI’s advantages, constraints, and the future.
  • Having basic skills in Octave programming to model the simple AI modules.
  • Understanding basic AI techniques to handle real-world problems.
  • Learning basic skills to use Rapidminer in the machine learning area.

Job Role Readiness

It will prepare learners in the following job roles to perform their responsibilities more effectively/ It will prepare learners for the following job roles:

  • AI and Machine Learning apprentice
  • AI and Machine Learning executives
  • Business transformers
  • Industry transformers
  • Business advisors/analysts

Who Should Attend

  • Almost all the businesses and industries that would like to employ AI and Machine Learning professionals.
  • All the businesses and industries that are going to transform their business model into an AI-driven one.
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This programme is part of

  • Advanced Professional Certificate in Applied Artificial Intelligence and Machine Learning

    • Types of Available Fundings

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

    Dr Ai Xin

    Dr Ai Xin

    Dr Ai Xin is currently a Lecturer with the School of Computing at the National University of Singapore (NUS). She has many years’ experience teaching Artificial Intelligence and Data Science courses such as machine learning, deep learning and data mining. She graduated from NUS with a PhD degree in Electrical and Computer Engineering. Her research focused on Game Theoretical Modelling, Optimization Methods, Algorithm Design and Wireless Networks. She worked at BHP Billiton Marketing Asia for eight years, gaining extensive industry experience in various functions such as risk management, supply chain management, and sales and marketing planning.

    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
    S$1,798.50 S$698.50 S$1,798.50 S$698.50 S$5,995.00
    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 for all short courses within a professional certificate in order 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. Maximum Candidature Period: Candidates who enrol for the professional certificates must complete the programme within three years from the start of their course. 

    Advanced Computing for Executives

    11 Research Link
    COM 3, #B1-07
    Singapore 119391
    Email: soc-ace@nus.edu.sg

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