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Description
Content:
This course will introduce data science tools and techniques to investigate problems related to infrastructure systems. The problems investigated in the course will span three topic areas in data science: choice modelling, machine learning, and simulation. These concepts will be taught using specific case-studies, with students working on real-life examples. Students will analyse data from diverse sources including historic travel diaries and trip records, surveys, and census data.
Teaching delivery:
This module is taught in 10 weekly interactive workshops.
Learning Outcomes
1. Understand and critically evaluate the potential and limitations of various data science techniques to assist in the management and operation of infrastructure systems.
2. Independently set-up and complete data-science investigations within the infrastructure context, including data preparation, selection of techniques, application, and validation.
3. Develop technical skills needed by MSc dissertations, as well as other future research and industry activities, that use analytical methods or modelling techniques to investigate engineering challenges.
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听Recommended readings
- Train, Kenneth. Discrete Choice Methods with Simulation / Kenneth E. Train. Second edition. Cambridge: Cambridge University Press, 2009. Available freely online at:
- Hastie, Trevor et al. The Elements of Statistical Learning听: Data Mining, Inference, and Prediction / Trevor Hastie, Robert Tibshirani, Jerome Friedman. Second edition. New York: Springer, 2009. Available听freely online at:
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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