Due to the exceptional circumstances caused by the COVID-19 pandemic, the learning activities, assessments and attendance requirements for this unit may be subject to late changes. Please refer to this unit outline regularly for up to date information and to notices in the unit’s Canvas site for any adjustments.
This unit of study offers students an introduction to civil engineering data analysis using examples of real-world transport operations applications. Students will develop skills to convert data into information for decision making including data ingestion, data structures, summarisation, visualisation, error analysis, and basic modelling. The data science skills will be taught using Python notebooks. In parallel with data science skills, this unit of study will introduce public transport system operations and planning. Lecture and reading content will provide a foundation of history, terminology and methods to assess the performance of public transport systems and make data-driven planning decisions. The datasets will be drawn from urban public transport applications, and explore real-world challenges in transport informatics.
|Academic unit||Civil Engineering|
|Assumed knowledge: ?||MATH1005 AND CIVL2700. Understanding of statistical inference. Familiarity with the urban transport network and basic concepts in transport studies.|
At the completion of this unit, you should be able to:
Unit outlines will be available 2 weeks before the first day of teaching for 1000-level and 5000-level units, or one week before the first day of teaching for all other units.