Data Science for Smart Cities
Cities become more dependent on the data flows that connect infrastructures between themselves, and users to infrastructures. Design and operation of smart, efficient, and resilient cities nowadays require data science skills. This course provides an introduction to working with data generated within transportation systems, power grids, communication networks, as well as collected via crowd-sensing and remote sensing technologies, to build demand- and supply-side urban services based on data analytics.
Topics
- Become familiar with urban big data and sensor data collection techniques. Develop intuition in various machine learning classification algorithms, as well as regression modelling. Foster critical thinking about real-world actionability from analytics. Develop intuition in various machine learning classification algorithms, as well as regression modelling. Learn how to use data science techniques in urban decision-making and scenario generation.
- Develop capabilities in a range of data science techniques. Use data analytics in the smart city domain. Think critically about how to assess analytics for cities. Gain the ability to solve problems in smart city research and practice.
Official catalogue course objectives and student learning outcomes
Prerequisites & course information
{'preRequisiteCourse': '1245672', 'concurrentPrerequisit': False}; {'preRequisiteCourse': '1245673', 'concurrentPrerequisit': False}; {'preRequisiteCourse': '1245671', 'concurrentPrerequisit': False}; {'preRequisiteCourse': '1245674', 'concurrentPrerequisit': False}
Sources
- Course catalogue ↗2026-2027