COURSE OBJECTIVES
Artificial Intelligence (AI) has been the focus of much attention in recent years, and stakeholders from diverse backgrounds have shown interest in it. This 2-week course aims to equip participants with a fundamental understanding of AI, skills and tools to assess the benefits and risks of AI policy for their local communities. Participants will also learn leadership skills focused on community building and social impact.
Participants will be guided to work on their own AI projects, targeting a problem identified in their community. They will also engage in meaningful discussions on measures the local government can take to maximize the social benefits of proposed AI initiatives while minimizing the risks.
In addition to classroom teaching and academic workshops, participants will undergo a series of leadership workshops and learning journeys focusing on community leadership. The leadership component aims to empower young people to build and support economically and socially healthy futures for their communities. Mentors and senior students will guide participants to identify social needs in the local community and endeavour to improve the lives of vulnerable groups or communities/ ecosystems with needs.
At the end of the programme, participants should be able to:
- Build solid foundation on Artificial Intelligence principles and its real-world use cases around the world;
- Understand policy tools and their application, limits and trade-offs, for assessing what constitutes a “good” AI public policy;
- Be able to use public policy tools to assess the benefits and risk of AI and its application to the society;
- Be able to formulate his/her own AI solution, and assess its benefits and risk for the local community.
Who Should Attend
This course is specially developed for High School Grade 11 students selected and nominated by National Achievement Center, the Ministry of Education, Culture, Research and Technology of the Republic of Indonesia, as part of BIM Overseas Undergraduate Preparation Program.
Pre-Requisites
Participants should be able to read, write and communicate fluently in English.
There are no specific pre-requisites in terms of math or computational science. Some exposure to calculus, linear algebra, and statistics would be useful.
Programme Schedule
Mode of Delivery
On-campus.
2-week face-to-face programme with 55 hours of academic component, 32 hours of leadership component and 12.5 hours of cultural immersion activities.
Mode of Assessment
Students will be assessed via a variety of assignments and assessments:
Academic component: Final Project on AI
Leadership component: Video assignment
Certificate of Completion
Successful participants who fulfill all program requirements, including meeting the minimum attendance and passing the assessment, will be awarded an e-Certificate of Completion and Assessment Report issued by NUS SCALE.