Inter-disciplinary Curriculums
Why this approach?
Critical thinking & problem-solving
Interdisciplinary curriculums can challenge students to think critically and creatively about problems and come up with innovative solutions. This can help students to develop important skills such as problem-solving, creativity, and critical thinking.
A holistic understanding of complex issues
Interdisciplinary curriculums can help students to see the connections between different disciplines and understand how they relate to one another. This can help students to develop a more comprehensive and nuanced understanding of complex issues.
Promoting collaboration & communication
Interdisciplinary curriculums often involve working with students from different disciplines, which can promote collaboration and communication skills.
What do we offer?
University AI+ course
This course is an introduction to Artificial Intelligence (AI) from an applied perspective. It begins by introducing basic concepts in machine learning or data science. After an introduction of basic concepts and techniques, the course illustrates both the potential and current limitations of these techniques with examples from a variety of applications. Students will explore these ideas in a final group project.
Pre-University STEAM course (for 16-18 years old)
STEAM course is designed as an interdisciplinary course, specifically, is designed to integrate multiple subjects and fields of study to provide college prep students with a well-rounded and holistic understanding of STEAM. In addition to core classes, this course incorporates traditional classroom instruction, hands-on learning opportunities, and real-world problem-solving.
Featured interdisciplinary projects
by alumni students
Analysing dogs’ emotions with vision Transformer
Track: Deep Learning & Neural Networks
Achieving equity in education through artificial intelligence
Track: Humanity, Arts & Digital Creativity
Art therapy for depressed people based on BCI
Track: Biotechnology Engineering
Text analytics in finance-stock forecasting model
Track: Investment & Quantitative Finance
Smart contracts and decentralised finance
Track: Big Data & Financial Technology
Causal inference in movie recommender systems
Track: Advanced Machine Learning
