This course will explore how to use randomized A/B/N experiments to compare alternative intervention components and to continuously enhance the design of digitally delivered interventions, so that these interventions are intelligently adaptive in trying to better help people change behaviour and achieve their goals. The course draws on Human-Computer Interaction topics around design and prototyping of interventions, Social-Behavioural Science theory and methods for understanding and impacting human behaviour, Artificial Intelligence applications like LLMs (Large Language Models) for designing and adapting interventions, Machine Learning algorithms for adaptively analyzing and adjusting experiments, and Statistical methods for analyzing traditional and adaptive A/B/N experiments.