AI And Machine Learning
Begins With Me
Date: 4 Aug, 5 Aug 2022 | 9am – 5.30pm | Online
Duration: 2 Days
Enter the world of artificial intelligence with this beginners AI course in Singapore. Gain understanding of machine learning and AI in a business context.
Course Overview
This course is designed to teach you what Artificial Intelligence (AI) is, and what its applications are. The learners will comprehend the 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. Learners by working on some simple practices and small-scale projects will understand practical uses of AI in business and daily life as well as its diverse applications and possibilities, including AI as a career. In doing so, learners will be also able to appreciate the challenges of AI. As it is an introductory course, learners do not have to be an IT expert or programmer to attend it.
This module is part of Professional Certificate in Artificial Intelligence for Non-AI Scientists
Course Objectives
- The course aims to equip learners with the knowledge and skills to:
- Define AI, machine learning and deep learning.
- Use AI utilities in various businesses and/or work contexts.
- Implement AI, machine learning and deep learning in their daily businesses.
Learning Outcomes
At the end of the course, the participants will be able to:
- Define the basic concepts of 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.
Topics
At the end of the course, the participants will be able to:
- Overview of Artificial Intelligence.
- Search
- Logic
- Machine Learning
- Deep Learning
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 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 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.
Dr Edmund Low
Dr Edmund Low
Dr Edmund Low is currently Senior Lecturer with the NUS College at the National University of Singapore.
He has nearly 20 years of academic and professional experience in the use of data-driven tools to answer questions in public health and the environment. His past projects include applying AI techniques and machine learning models for environmental modelling and impact assessment. He currently heads the quantitative reasoning domain at USP, and teaches courses on statistical methods, data science and machine learning. As an educator, Edmund is a multiple recipient of both the USP Teaching Excellence Award, as well as the NUS Annual Teaching Excellence Award. Edmund holds a PhD in Environmental Engineering from Yale University.
Hear from the Participants
“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
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.
NTUC members enjoy 50% unfunded course fee support for up to $250 each year (or up to $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 Code:
TGS-2020503220 (Synchronous e-learning)
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or older