Course Description

Artificial Intelligence is rapidly reshaping how we think, create, and solve problems across disciplines. From automation to creative expression, AI is transforming not only industries but also the way we engage with the world around us. This course explores AI as a tool for critical inquiry, design thinking, and communication—especially in the context of urban life and the built environment.

You’ll build foundational skills in computational and AI literacy, learning how data is structured, how machine learning models are trained, and how neural networks operate. Starting with basic pattern recognition, you’ll construct and interpret simple models to solve classification problems. The course then introduces generative techniques, allowing you to experiment with AI systems that produce new text and imagery based on learned patterns.  

A key focus of the course is ethical and responsible AI use. Through interactive demonstrations and real-world case studies, you’ll examine issues such as algorithmic bias, fairness, explainability, and the societal impacts of automation. These themes are explored through examples from media, public systems, and the urban environment.

Coursework includes both individual and group-based activities. You’ll complete case analyses, hands-on exercises, and communication-focused assignments. A final team project challenges you to apply AI creatively to a built environment problem—whether visualising public space, analysing spatial data, or developing an AI-assisted design concept. Projects are shared through a recorded demo and short reflective brief.  By the end of the course, you’ll not only understand how AI works, but how to work with it—critically, creatively, and responsibly. You’ll leave with practical skills, ethical awareness, and the confidence to apply AI in real-world academic and professional contexts.

Course Learning Outcomes

On completing the course, students will be able to:

1. Explain how AI’s foundational concepts, such as neural networks, generative models, and reinforcement learning, are used to solve real-world design challenges across different building design scales.
2. Analyse the ethical concerns related to AI, including bias, transparency, and fairness, and propose responsible approaches to mitigate these issues in AI-driven applications.
3. Apply AI tools and methodologies to create innovative design solutions that address sustainability challenges within the built environment, specifically aligned with the UN Sustainable Development Goals.
4. Collaboratively develop AI methods, using group projects, peer feedback, and desk crits to refine AI- assisted design strategies and enhance teamwork skills.
5. Demonstrate the ability to communicate AI-assisted design concepts effectively through presentations, interactive visualisations, and documentation, showcasing both creative problem-solving and ethical considerations.

Offer Semester and Day of Teaching

Second semester (Wed)