Dates: 15 Nov, 17 Nov 2023 | 9am-5.30pm | Online
Duration: 2 Days
Course Overview
One of today’s most important technologies that impacts every business from education to healthcare to finance to management is Artificial Intelligence (AI). AI can also help to boost one’s job and career prospects, as one will be able to apply it for problem-solve and enhancing productivity.
This course aims to equip participants with the knowledge and skills to use AI techniques to solve real-world problems. It focuses on two important AI subdomains, logic and search. Logic helps us to develop rules-based expert systems and in this course, we will focus on Fuzzy Logic and train participants on how to design and implement fuzzy rules-based expert systems. Search helps us to solve complicated optimisation problems and in this course, we will focus on evolutionary algorithms, which are one of the most advanced and capable optimisation algorithms. Participants will be taught how to design and develop evolutionary algorithms to solve optimisation problems.
This course is part of Professional Certificate in Artificial Intelligence and Machine Learning Basics.
Learning Outcomes
At the end of this course, participants will be able to:
• Extract logic rules for different problems
• Design and implement basic rules-based fuzzy expert systems
• Design and implement basic evolutionary algorithms
• Solve typical optimisation problems using evolutionary algorithms
Who Should Attend
Business and market analysts, as well as IT technicians.
Prerequisites
Basic AI knowledge and basic programming skills
Course Convener
(Click photo to view biography)
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
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.
This course is eligible for Union Training Assistance Programme (UTAP).
NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. Please click here for more information.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Code
TGS-2020504369 (Synchronous e-Learning)
TGS-2020513880 (Classroom)
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or older
