Publication: AI Builders: Teaching Thai Students to Build End-to-End Machine Learning Projects Online
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Issued Date
2021-01-01
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2-s2.0-85125943347
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Mahidol University
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SCOPUS
Bibliographic Citation
TALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings. (2021), 565-572
Suggested Citation
Charin Polpanumas, Peerat Limkonchotiwat, Benyapa Matupumanon, Chompakorn Chaksangchaichot, Natkrita Chumlek, Nattakarn Phaphoom, Pakin Siwatammarat, Pined Laohapiengsak, Sukrit Amornpornwiwat, Witchapong Daroontham, Ekapol Chuangsuwanich, Kowin Kulruchakorn, Sarana Nutanong, Titipat Achakulvisut AI Builders: Teaching Thai Students to Build End-to-End Machine Learning Projects Online. TALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings. (2021), 565-572. doi:10.1109/TALE52509.2021.9678620 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/76700
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Title
AI Builders: Teaching Thai Students to Build End-to-End Machine Learning Projects Online
Abstract
Teaching machine learning (ML) and artificial intel-ligence (AI) for middle-to-high school students is crucial to build a good sustainable research community. However, the current ML education system and ecosystem in developing countries, including most countries in South East Asia (SEA), is still far from reaching for most students. Students, especially where English is their second language, still struggle to learn ML and AI even in the global accessibility of AI classes online. Thus, teaching AI in these circumstances can be challenging yet rewarding. Here, we organized a nine-weeks online summer school, called AI Builders, aiming to teach ML and AI to Thai students. We combined existing ML and AI curricula in conjunction with end-to-end ML projects. We provided recap classes in native language, locally collected datasets, mentorship for projects, guest lectures, and career discussions in our program. Students were able to satisfactory understand ML concepts and produced meaningful projects even though some might not fully had the necessary background at the start of the program. We discussed possible improvements for future iterations.