Content, progress and pedagogy of the module

Learning objectives

Knowledge

• Can account for patterns in data and their underlying mathematical structure
• Can explain how patterns can be described using features
• Can describe the elements of a machine learning system
• Can explain how multivariate data can be modelled using probabilistic and parametric descriptions
• Can account for neural networks and deep learning

Skills

• Can design and test a machine learning system
• Can apply parametric and non-parametric classification techniques to multivariate data
• Can analyse and describe the underlying density function of a dataset
• Can use methods for selecting features and reduction of data dimensionality
• Can apply methods for testing and evaluating machine learning systems

Competences

• Can demonstrate an understanding of theories and methods within machine learning
• Can perform feature analysis and apply classification techniques to specific biomedical problems based on multivariate data

Type of instruction

The module is taught, cf. §17 of the study programme

Exam

Exams