Welcome to the course Multivariate data analysis in engineering!

The application of multivariate data analysis methods and a tremendous increase in available computational power have opened great opportunities to address present and future engineering challenges. If you want to learn how modern multivariate data analysis, including artificial intelligence (AI) and machine learning algorithms, can be used to address engineering challenges - then this course is for you. The course will provide you with the essential knowledge that enhances your capabilities to solve complex engineering problems, within fields such as waste management, energy, agriculture, water management, weather forecasting – and thereby contributing to sustainable development.

Course aim

The purpose of the course is to provide essential knowledge and understanding of the principles of multivariate data analysis methods in engineering. The knowledge is applied to multivariate analysis, modeling, and interpretation of results related to different fields of engineering using data exploration, artificial intelligence (AI), and machine learning algorithms.

Course content

The course mainly addresses the following: explanatory data analysis and interpretation, multivariate qualitative and quantitative data analysis and interpretation using artificial intelligence (AI) and machine learning (ML) algorithms, multivariate time-series data analysis, and interpretation.

Course syllabus

Visit our webpage with the course syllabus to learn more about the objectives, learning outcomes, specific requirements, and examination. More information about how the course is embedded in programme can be found in the section Course placement in the programme (link).

Sustainable development goals addressed