Data Analytics for Civil Engineers

About

Civil engineering is increasingly data-driven. This course introduces students to data analysis, data mining, and machine learning approaches tailored for civil engineering applications. Students will learn how to extract, process, and interpret diverse data sources such as sensor-based monitoring of infrastructure, environmental measurements, geographic information, and even social media sentiment data related to infrastructure usage. By the end of the course, participants will understand key machine learning techniques, apply them to real datasets, and communicate their findings using effective data visualization. Practical training will be conducted in R.

Course leader

Mohamed Abdelfattah

Target group

International Bachelor and Master students in:

-Civil Engineering
-Environmental Engineering
-Urban and Regional Planning
-Data Science with interest in engineering
-Related engineering disciplines

Course aim

By the end of the course, students will be able to:

-Understand the role of data-driven approaches in civil engineering.
-Apply machine learning methods (classification, regression, clustering) to civil engineering datasets.
-Perform data preprocessing, feature extraction, and visualization.
-Critically evaluate the performance of models.
-Communicate insights from data to support design and decision-making in civil engineering projects.

Fee info