6 Jan 2023 | 9am-5.30pm | Classroom Learning
Duration: 1 Day
The Internet of Things (IoT) technology revolution today is what the internet revolution was in the 90s. It is completely changing the way we live, work and play. Whatever industry or field you are in, a basic understanding of the various components of the IoT value chain is crucial. This course will help you answer the “why, how and what” questions for IoT.
The course will start by exploring examples and case studies on why we need IoT and how it can impact our day-to-day work in various industries. You will then learn about the various components of an IoT solution – things, networks, cloud and software – through hands-on experiments using open source IoT development boards and IoT cloud software. The course will end by discussing the real-world challenges of deploying IoT solutions and brainstorming use cases that you would like to implement once you go back to work.
The course uses a unique mix of theory, hands-on experiments, brainstorming and challenges to ensure you absorb and retain the knowledge and skills learned during the course.
This module is part of Professional Certificate in Emerging and Disruptive Technologies.
The course aims to:
- Introduce absolute beginners to the world of IoT and connected hardware
- Inspire participants to start their Corporate IoT or Digitalisation projects
- Provide hands-on experience on the popular IoT Wi-Fi Microcontrollers
- Equip participants with the skills to create an end-to-end IoT prototype solution within a day
- Brainstorm IoT ideas and applications for participants’ respective industries
At the end of the course, participants will be able to:
- Conceptualise IoT solutions for their business cases
- Independently create IoT proof of concept demonstrations
- Choose the right IoT technologies for their use cases
- Estimate the effort and resources required to roll out IoT projects
Who Should Attend
Executives, Managers & Leaders
- Basic computer skills
- Knowledge of high school physics – electricity
(Click their photos to view their short biographies)
Assoc Prof Tan Wee Kek
Assoc Prof Tan Wee Kek is currently an Associate Professor in the Department of Information Systems and Analytics at the School of Computing, National University of Singapore. He is also currently serving as an Assistant Dean (Student Life) in the School of Computing, and a Fellow and EXCO member of the NUS Teaching Academy. He graduated with a Doctor of Philosophy in Information Systems in July 2013 and a Bachelor of Computing in Information Systems (1st Class Honours) in July 2007, both from the National University of Singapore. Prior to this, he attended Singapore Polytechnic and graduated with a Diploma in Computer Information Systems with Merit in July 2001.
His current primary research interests focus on consumer-based information technology (e.g., online decision aids, social computing, virtual worlds and consumer cloud services). Most of his research is based on design science, a well-established problem-solving paradigm that has been widely adopted in information systems research. His current secondary research interests focus on information systems education.
His work has been published or is forthcoming in journals such as Journal of the American Society for Information Science and Technology (JASIST), Decision Support Systems (DSS), Communications of the Association for Information Systems (CAIS), and Journal of Information Systems Education (JISE). His work has also been presented or is forthcoming in conferences such as ACM SIGMIS Computer Personnel Research Conference (SIGMIS-CPR), IFIP Working Group 8.2 Working Conference (IFIP WG8.2), European Conference on Information Systems (ECIS), Americas Conference on Information Systems (AMCIS), and International Conference on Human-Computer Interaction (ICHCI).
He has won the faculty level Research Achievement Award in 2013 and was a nominee for the ACM SIGMIS 2009 Magid Igbaria Outstanding Conference Paper of the Year.
His current teaching interests include imparting senior undergraduate students with knowledge and skills to develop enterprise information systems as well as teaching them principles of information security management, and concepts of mobile and ubiquitous commerce.
He has won the University level Annual Teaching Excellence Award for AY 2009 to 2012. In addition to this, he has also won the Faculty Teaching Excellence Award for AY 2008 to 2011 as well as the Faculty Best Teaching Assistant Award for AY 2007/2008. For his sustained commitment to teaching excellence, he has been placed on the Faculty Teaching Excellence Award Honour Roll for AY 2010/2011 and University level Annual Teaching Excellence Award Honour Roll for AY 2012/2013.
He is presently the lead faculty mentor of the NUS BiZiT Society, a student special interest group on business and information technology.
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.
Course Fee Breakdown
Singapore Citizens39 years old or younger
Singapore Citizen40 years old or older