- 7 video lessons (35 Mins)
Browse Course Chapters
2.Big Data4 mins
3.Data Processing5 mins
4.Artificial Intelligence6 mins
6.Data-Driven Decision Making5 mins
What You Will Learn
- The function and application of urban informatics
- The steps in processing data in urban informatics
- Concepts of deep learning and machine learning
- The role of artificial intelligence in urban informatics
- The use of visualization techniques in urban informatics
- The application of urban informatics in smart city case studies
Building from foundational concepts developed in the "Introduction to Smart Cities" course, "Introduction to Urban Informatics" introduces viewers to a relatively new field that uses emerging data-types to better understand how cities see, feel, think, and work. The Internet of Things and Big Data are making cities transparent, conscious, and connected. Urban informatics uses iterative analysis and evaluation of smart city data to understand outcomes and improve data-driven decisions. In a sense, urban informatics is the engine that updates and optimizes smart cities and, by extension, urban life.
This course is structured around the six steps of urban informatics: data collection, processing, analysis, visualization, data-driven decision-making, and outcome evaluation. Through case studies, this course explores how emerging data and big data sources are changing the planning process.
Join course instructor Amir Hajrasouliha in an exploration of data processing, including cloud computing, open data protocols, and string processing. Hajrasouliha also introduces the basic concepts of machine learning and artificial intelligence. Course participants will also learn about emerging visualization techniques and a number of urban informatics case studies affecting the everyday life of citizens and the efficiency of cities. By the end of this course, viewers will have a basic understanding of urban informatics and can begin to envision more sustainable, efficient, and just cities with the help of data.
Learn these skills
- Data Analysis
- Data Visualization
- Modeling & Simulation
- Research Methods