Course Objectives: Upon completion of the course, students will be able to: Apply analytics and AI techniques (including machine learning, digital twins, and IoT data) to optimise energy use, reduce emissions, and enhance occupant well-being in smart buildings. Analyse and interpret real-world smart building data for sustainable and adaptive solutions. Design and evaluate AI-driven solutions for predictive maintenance, occupant comfort, and environmental quality. Integrate multiple data sources and technologies to support sustainable smart living applications. Competencies: Ability to apply advanced analytics and AI tools in smart building contexts. Skill in processing and interpreting IoT-generated datasets. Capability to design and implement predictive models for operational efficiency. Proficiency in evaluating environmental and occupant comfort metrics using AI methods. Team-based problem-solving and project execution skills in applied smart living scenarios.