This is an AI for Curriculum activity where students are introduced to the topic of Natural Language Processing (NLP), as well as its application in the analysis of sustainability reports. This example of a real-world application of NLP serves to illustrate the limitations, issues and trade-offs surrounding machine learning.
This micro-course is designed for high school and junior college students to explore how Natural Language Processing (NLP) is used in analysing sustainability reports, amongst other use cases. Students will understand how machine learning and artificial intelligence play a part in automating tasks and scaling up solutions. Students should also gain an appreciation of the limitations and issues surrounding machine learning tasks. Learning the drawbacks of machine learning models and understanding trade-offs are important skills to influence decision-making processes in the future when working with machine learning tasks.
Structure Overview and Typical Completion Time
This course consists of 7 lessons.
The estimated course learning time is 2 hours.
There will be no e-certificate/badge upon completion of this micro-course.
Chan Kuang Wen
Chemistry Educator, Raffles Institution
Kuang Wen is a Chemistry educator and teaches junior college (JC) chemistry. His interests lie in sustainability education and using education technology to enhance teaching and learning (T&L), as well as to increase productivity. He is also interested in incorporating machine learning and artificial intelligence into sustainability education and educational technology. Previously, Kuang Wen read an MRes in Green Chemistry, Energy and the Environment at Imperial College London, United Kingdom. His undergraduate study in Chemistry was at the National University of Singapore.
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