Explainable Artificial Intelligence Fundamentals
Dates: To be advised
Duration: 2 Days
Course Overview
Algorithms in Artificial Intelligence (AI) can be categorized into two types: white-box and black-box algorithms. White-box models generate results that are easily comprehended by domain experts. Conversely, black-box models are challenging to explain and comprehend, even by domain experts. EXAI algorithms embody the principles of transparency, interpretability, and explainability. The role of AI in our lives and businesses will become increasingly important, making it essential that AI systems have outcomes and decisions that are explainable and understandable.
This course is part of Professional Certificate in Artificial Intelligence for Business.
Course Objectives
After completing this short course, the participants will be able to:
- Articulate EXAI and its applications
- Realize the importance and applications of EXAI
- Define different types of explainability
- Recognize when explainability is necessary
Who Should Attend
AI practitioner, ICT Engineers, Business Managers
Prerequisites
- Basic AI and Machine Learning knowledge
Course Convener
(Click their photos to view their short biographies)
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.
Mr Raju Chellam

Raju Chellam
Mr Raju Chellam is a Fellow of Advanced Computing for Executives (ACE) at the NUS School of Computing. He is the Chief Editor 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).
He is Hon Chair of Cloud & Data Standards at IT Standards Committee (IMDA/ESG). He is also on the APEC DARE (Data Analytics Raising Employment) International Advisory Panel, and on the Credence DTRS (Data Trust Rating System) Expert Panel. He was conferred as an SCS Fellow in March 2018.
Raju is Hon Vice President of the SCS Cloud Chapter, and former Vice Chair of SGTech’s Cloud & Data Chapter. He is Vice President (New Technologies) at Fusionex Group, a leading software company that specializes in ABC (AI, Big Data Analytics, & Cloud ). Raju has been in the IT industry for 40 years. He was previously Head of Big Data & Cloud Practice – as well as Healthcare & Government solutions – at Dell EMC South Asia (covering Asean, IndoChina, Mongolia & all South Asian countries except India).
Prior to Dell, he was Managing Director of TechTrenders Asia, an 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.
Course Fees
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Codes
TGS-2022012746 (Classroom Learning)
TGS- 2022012347 (Synchronous e-learning)
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or olderYou may also like to view:
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