Introduction
This two-day project-based learning professional development will be designed to introduce artificial intelligence (AI) fundamentals. Through this course, participants will engage in hands-on activities to gain a deeper understanding of AI and its applications in education
Synopsis:
Artificial intelligence (AI) encompasses human-like problem-solving and decision-making abilities and is typically implemented through man-made systems, including computer programs. Its application spans diverse domains such as education, healthcare, law enforcement, and the arts. Given the influence and recent democratization of AI systems, it is imperative to equip individuals with the essential conceptual knowledge and competencies required for success as professionals, innovators, consumers, and responsible citizens. This two-day project-based learning PD will be designed to introduce AI fundamentals and its applications in education. Through this course, students will engage in hands-on activities to gain a deeper understanding of human-AI collaboration.
Objectives:
- Develop conceptual knowledge about what is artificial intelligence (AI) and how it’s used in the real-world.
- Understand various components of machine learning that powers AI systems, including data, algorithm, model and prediction.
- Critique the benefits and risks of AI usage in everyday lives, with particular relevance to educational contexts.
- Gain experience with developing and deploying an AI application for education (AIED).
All educators
Standard Course Fee: S$779.35
| MOE Educators* | Non-MOE Educators** | S'poreans & PRs (aged 21 and above) (Up to 70% funding) | SkillsFuture Mid-Career Enhanced Subsidy1 (MCES) (S'poreans aged 40 and above) (Up to 90% funding) | Enhanced Training Support for SMEs (ETSS) (Up to 90% funding) | Public | |
|---|---|---|---|---|---|---|
| Full course fee | S$130.00 | S$715.00 | S$715.00 | S$715.00 | S$715.00 | S$715.00 |
| Cat-A SSG Funding | - | - | (S$500.50) | (S$500.50) | (S$500.50) | - |
| Nett course fee | S$130.00 | S$715.00 | S$214.50 | S$214.50 | S$214.50 | S$715.00 |
| 9% GST on nett course fee | S$11.70 | S$64.35 | S$19.31 | S$19.31 | S$19.31 | S$64.35 |
| Copyright fee | S$1.09 | S$1.09 | S$1.09 | S$1.09 | S$1.09 | S$1.09 |
| Total nett course fee payable, including GST and copyright fee | S$142.79 | S$780.44 | S$234.90 | S$234.90 | S$234.90 | S$780.44 |
| Less additional funding if eligible under various schemes | - | - | - | (S$143.00) | (S$143.00) | - |
| Total nett course fee payable, including GST, copyright fee and after additional funding from various funding schemes | S$142.79 | S$780.44 | S$234.90 | S$91.90 | S$91.90 | S$780.44 |
*MOE Educators include MOE & Direct Hire Staff from Independent, Specialised Independent and Specialised Schools.
**Non-MOE educators refer to those from SSP, SOTA, polytechnics, ITE, LASALLE, NAFA, University of the Arts Singapore, government-affiliated educational institutes, and autonomous universities.
Tanmay Sinha
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ANNOUNCEMENT(s):
I am always on the lookout for PhD/EdD students. If you are interested in doing impactful work at the intersection of emotions, learning through problem-solving, and AI for education, feel free to reach out for any queries and discussions on overlapping research interests! A short writeup of current projects can be found here: https://lnkd.in/gmmztMBC. Next application cycle in second half of 2025!
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Dr. Tanmay Sinha is an assistant professor at the National Institute of Education, Nanyang Technological University in Singapore. He obtained a master’s degree in artificial intelligence from Carnegie Mellon University (USA) and completed his doctoral work in the learning sciences at ETH Zurich (Switzerland). Tanmay served as executive director for the first ETH-EPFL joint doctoral program in the learning sciences in Switzerland during its formative years (2021-2023), where he co-developed the academic program strategy, formulated and taught courses on learning sciences foundations and artificial intelligence for education.
Tanmay's research has appeared in flagship avenues such as Journal of the Learning Sciences, Journal of Educational Psychology, Review of Educational Research, Learning and Instruction, and Cognitive Science. His research has received further accolades at three international conferences, including Empirical Methods for Natural Language Processing (shared task winner in modeling large scale social interaction in MOOCs), Intelligent Virtual Agents (best student paper), European Conference on Technology Enhanced Learning (best paper nominee). Tanmay has served as a peer-reviewer for journals such as Nature Scientific Reports, Journal of the Learning Sciences, Journal of Educational Psychology, Learning and Instruction, Instructional Science, Journal of Learning Analytics, International Journal of Computer Supported Collaborative Learning, Computers and Education, to name a few. His research has also garnered attention from prestigious media outlets like The New York Times, Times Higher Education, and the World Economic Forum.
