Dates:
4 Oct, 6 Oct 2023 | 9am – 5.30pm | Online
This intake is part of Professional Certificate in Artificial Intelligence and Machine Learning Basics
26 Feb, 27 Feb 2024 | 9am – 5.30pm | Online
This intake is part of Professional Certificate in Artificial Intelligence and Machine Learning Foundation for Executives
Duration: 2 Days
Course Overview
This course is designed to teach you about Artificial Intelligence (AI) and its applications. Learners will comprehend basic AI-related terms such as Machine Learning, Deep Learning, and Expert Systems which will play a key role in the future of technology and science. By working on some simple practices and small-scale projects, participants will be able to understand the practical uses of AI in business and daily lives as well as its diverse applications and possibilities, including AI as a career. In doing so, learners will be able to appreciate the challenges of AI. As this is an introductory course, participants do not have to be an IT experts or programmers in order to attend it.
This course is part of Professional Certificate in Artificial Intelligence and Machine Learning Basics and Professional Certificate in Artifical Intelligence and Machine Learning Foundation for Executives.
Course Objectives
At the end of the course, the participants will be able to:
• Define the basic concepts of Artificial Intelligence (AI)
• Describe the important challenges in the field of AI
• Interpret important AI approaches to problem solving
• Describe search and optimization techniques and the heuristics
• Understand machine learning and apply it to the context of their businesses and/or work contexts
• Explain deep learning
• Identify where and how AI (and Machine Learning and Deep Learning) is applicable to their own business challenges
• Identify the impacts of implementing AI to their businesses
Who Should Attend
Anyone who is interested in AI.
Prerequisites
General degree; basic knowledge in matrices and statistics; able to use internet
Course Conveners
(Click photos to view biographies)
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 on teaching Artificial Intelligence and Data Science courses, e.g. machine learning, deep learning, data mining and etc.
She graduated from NUS with a PhD degree on Electrical and Computer Engineering. Her research focused on Game Theoretical Modelling, Optimization Methods, Algorithm Design and Wireless Networks.
She worked in BHP Billiton Marketing Asia for eight years and gained a lot of industry experience through different functions, e.g. risk management, supply chain management, sales and marketing planning and etc.
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.
What Our Participants Say
“This course was a good introduction of AI and ML and the real-world applications.”
– Agatheeben Amarasingam
“This was a good introduction of AI. The course provided knowledge of various algorithms that one should know and interest before diving deeper into AI. Although it was only 2 days, I gained a better understanding in implementing AI development.”
– Tang Tung Ngie
“The course has provided me a deep insight about Artificial Intelligence and Machine Learning including the origin and in trend technology. Having this knowledge will enable us to be more proactive to deal with information and data that we have. It also helps us to understand the technology that we used in our daily life.”
– Gimun Solomon Yang
“This is indeed a fantastic, engaging, and interactive course for beginners to gain knowledge and context on AI, as well as to open up possibilities with the power of AI! It is very well-put together and easy to follow.”
– Goh Yuan Hao Lucas
“The course serves as a start for beginners to learn about machine learning and AI. It is interesting and easy for people with no background to learn. Thank you Dr Amir.”
– Fiona
“It is a must take lesson for people who are new to this course but with some background in data analysis.”
– Loo Lih Chyun
“Good course to give an intro to AI”
– Tay Hui Chun
“A good course for IT practitioners who would like to further develop expertize in AI/ML”
– Moy Keen Choy (KC)
Course Fees
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
GST shall apply at prevailing rates
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
NTUC members enjoy 50% unfunded course fee support for up to S$250 each year (or up to S$500 for NTUC members aged 40 years old and above) when you sign up for courses supported under UTAP (Union Training Assistance Programme). Please visit e2i’s website to find out more.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Codes
TGS-2020506039 (Classroom Learning)
TGS-2020503220 (Synchronous e-learning)
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or older
