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Advanced Professional Certificate

Advanced Professional Certificate in Artificial Intelligence and Machine Learning for Executives and Technopreneurs

Training Roadmap


Completion of Stages 1 to 3 curricula earns the participant an Advanced Professional Certificate in this programme.
  • Please click on the individual courses for more details.

Programme Objectives

This Advanced Professional Certificate will equip learners with the following competencies:

  • Articulating Artificial Intelligence (AI) and Machine Learning (ML)
  • Understanding the implementation approaches, pros and cons, and ethical issues in the wide spectrum of AI and ML applications
  • Articulating the Robotics Process Automation and decision support systems
  • Learning how to develop the real-world Supervised and Unsupervised Machine Learning modules

Who Should Attend

  • High-level and intermediate-level managers in all businesses and industries who wish to utilize AI and Machine Learning in their business
  • Fintech and high-tech Business advisors

Prerequisites

At least a polytechnic diploma (or equivalent).

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Types of Available Fundings

  • Enhanced Training Support
  • SFEC
  • PSEA

    • Instructors


    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 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 Edmund Low

    Dr Edmund Low

    Dr Edmund Low is currently Senior Lecturer with the NUS College at the National University of Singapore. He has nearly 20 years of academic and professional experience in the use of data-driven tools to answer questions in public health and the environment. His past projects include applying AI techniques and machine learning models for environmental modelling and impact assessment. He currently heads the quantitative reasoning domain at USP, and teaches courses on statistical methods, data science and machine learning. As an educator, Edmund is a multiple recipient of both the USP Teaching Excellence Award, as well as the NUS Annual Teaching Excellence Award. Edmund holds a PhD in Environmental Engineering from Yale University.

    Dr Natarajan Prabhu

    Dr Natarajan Prabhu

    Dr Natarajan Prabhu is currently a senior lecturer in the School of Computing at the National University of Singapore. He has 10+ years of experience in teaching for master’s degree programs, undergraduate modules, and continuing education courses. Before joining NUS, he was teaching at DigiPen Institute of Technology, where he taught AI for Games, Digital Image Processing, Machine Learning, Deep Learning, Data Structures, etc. In DigiPen, he developed a master’ degree program for Computer Vision that primarily prepares graduate students to work in the CV industry. After joining NUS as a lecturer, he is currently working on developing and teaching an AI module for non-CS students in Blended learning. He graduated with a Ph.D. degree from NUS in 2013, a master’s degree, and a bachelor’s degree from Anna University in 2008 and 2006, respectively. His Ph.D. thesis was about automatically controlling and coordinating multiple active cameras in surveillance networks. During this time he has gained rich experience in building multi-camera surveillance systems. He has received “Best PhD Forum Paper” award from International Conference on Distributed Smart Cameras (Hong Kong, 2012) and “Research Achievement Award” from School of Computing, NUS (2012).

    Dr Akshay Narayan

    Dr Akshay Narayan

    Akshay Narayan is a senior lecturer at the School of Computing in NUS. He received his Ph.D. degree from NUS in 2020 and M.Tech from IIIT-Bangalore in 2012. Akshay teaches senior undergraduate/graduate level AI Planning and Decision Making and introductory Software Engineering modules at SoC. Akshay is broadly interested in AI planning, sequential decision making, and its applications. His current research is on transfer learning in reinforcement learning. Previously he has worked in the area of cloud computing. Some of his past projects include smart metering and chargeback as applied to cloud systems, incorporating power awareness in cloud metering, workload analysis for virtual machine sizing and location in private clouds, and QoS monitoring and response in cloud systems.

    Mr Mario Favaits

    Mr Mario Favaits

    Over the past 25 years, Mr Mario Favaits held several sales and operations (P&L) leadership positions at various multinationals across different industries including Enterprise, Automotive, Public Transport, and Software. Currently, he serves as the Executive Director of Services Sales APJ at Crayon, a fast-growing, listed, Oslo-based IT powerhouse. Crayon helps customers to innovate with scalable AI. Prior to joining Crayon, Mario held leadership positions at Alstom, Continental, Siemens, Oracle, and SMRT, Singapore’s largest Public Transport Operator. Between 2014 and 2019, he was a member of SMRT’s executive leadership team. In 2019, Mario joined the AI and IoT startup scene as an advisor and/or investor. Mario is the co-chair of EuroCham’s Digital Economy Committee and is the author of an online AI course for Executives, in collaboration with Deloitte. He holds a Master of Science in Mechanical and Electrical Engineering from the University of Brussels, an MBA from the University of Antwerp Management School, and a Master of Laws from the University of Liverpool.

    Mr Raju Chellam

    Mr Raju Chellam

    Raju Chellam is a Fellow of ACE (Advanced Computing for Executives) at NUS School of Computing. He is the Editor-in-Chief of the AI E&G BoK (AI Ethics & Governance Body of Knowledge), an initiative by the SCS (Singapore Computer Society) & IMDA (Infocomm Media Development Authority) of Singapore. He was conferred as an SCS Fellow in March 2018. Raju is Hon Chairman of Cloud & Data Standards at ITSC (IT Standards Committee), Hon Vice President of SCS Cloud Chapter, and on the Exco of SCS AI & Robotics Chapter. He writes a regular column on tech in The Edge (Malaysia), Dataquest (India), and occasionally in The Straits Times (Singapore). Raju has been in the IT industry for the past 43 years. He was on the APEC DARE (Data Analytics Raising Employment) International Advisory Panel (2016 to 2023), and on the SWF (Singapore Writers Festival) Advisory Panel (2021 to 2023). Raju was previously Head of Big Data & Cloud Practice – as well as Healthcare & Government Solutions – at Dell South Asia (ASEAN, Indo-China, Mongolia & all South Asian countries except India). Prior to Dell, he was Managing Director of TechTrenders Asia, a boutique advisory that helped companies migrate legacy apps to the cloud. He has previously worked in Hewlett-Packard (APJ Director of Comms), AMI Partners Inc (APAC Vice President) and as the BizIT Editor of The Business Times, Singapore, for a decade.

    Programme Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old or younger 40 years old or older
    S$10,767.50 S$7,117.50 S$10,767.50 S$7,117.50 S$19,892.50
    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 an advanced professional certificate 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.