Explainable Artificial Intelligence Fundamentals
Date: 8 Mar, 9 Mar 2023 | 9am-5.30pm | Online
Duration: 2 Days
Explainable Artificial Intelligence (XAI or EXAI) is a term refers to studies which try to demystify AI functions. The algorithms used in Artificial Intelligence (AI) can be categorized into white-box and black-box algorithms. White-box models provide results that are understandable for experts in the domain. Black-box models, on the other hand, are extremely hard to explain and can hardly be understood even by domain experts. XAI algorithms are considered to follow the three principles: – transparency, interpretability, and explainability. AI is going to play an essential role in our lives and businesses. Hence, AI systems with their outcomes and decisions explainable and understandable will be getting more essential as well.
This module is part of Professional Certificate in Artificial Intelligence for Business.
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 practicioner, ICT Engineers, Business Managers
- Basic AI and Machine Learning knowledge
- Basic Python language skill
(Click their photos to view their short biographies)
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 the 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.
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.
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TGS-2022012746 (Classroom Learning)
TGS- 2022012347 (Synchronous e-learning)
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Course Fee Breakdown
Singapore Citizens39 years old or younger
Singapore Citizen40 years old or older