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 enhance 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.
At the end of the 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
- Getting familiar with the course
- A brief review of AI
- AI’s Applications
- Logic and Decision Making
- Different models of logic
3. Expert Systems
- Designing a fuzzy expert system (FES)
- Implementing a FES
- Search to solve a problem
- Classification and recognition via search
- Local search and optimisation
- Evolutionary algorithms introduction
2. Evolutionary Algorithms (EA)
- Genetic Algorithms (GA)
- GA concepts
- GA applications and use cases
3. Optimisation using EA
- Designing a GA for optimisation
- Implementing a GA for optimisation
Orange, Octave, Python
Basic AI knowledge and basic programming skills
Who Should Attend
IT Technicians, Business and Market Analysts
Mode of Training
On-campus or Online (Live)
Dr. Amirhassan Monajemi
Amirhassan Monajemi is a Senior Lecturer in AI and Data Science with the School of Continuing and Lifelong Education (SCALE) at the National University of Singapore (NUS). 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 1968 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.