Course content

This course introduces the growing field of machine learning and its application to psychological research and practice. The course will provide a conceptual understanding and a solid theoretical foundation of different types of machine learning. In particular, the course will review and provide hands-on training in both supervised (e.g., support vector machines and regression trees) and unsupervised (e.g., cluster analysis and mixture modelling) machine learning methods and apply these to both classification and regression problems. Importance will be placed on using cross-validation to remedy problems with over-fitting. The course will also include an introduction to neural networks and deep learning.

Learning outcome

Knowledge:

• The student understands how machine learning can benefit psychological research.
• The student knows the distinction between supervised and unsupervised learning and can produce examples for both.
• The student can reflect on the bias-variance tradeoff and relate it to overfitting and cross-validation.

Skills:

• The student is able to select an appropriate method from machine learning to conduct complex data-analytic tasks relevant to psychological research.
• The student is able to successfully apply selected supervised learning methods to data-analysis problems occurring in psychological research.
• The student is able to successfully apply selected unsupervised learning methods to data-analysis problems occurring in psychological research.
• The student is able to use relevant software to conduct machine learning-based analyses.

General competence:

• The student has knowledge to critically evaluate scientific works using machine learning to solve problems in psychology.
• The student can critically reflect on the usefulness of different machine learning tools to help making progress in psychological research.
• The student can evaluate and communicate the results of a machine-learning based analysis to a scientific audience using adequate graphical and numerical representations.

Learning methods and activities

Forelesninger og lab-øvinger

Compulsory assignments

• Optional assignments

Specific conditions

Required previous knowledge

PSY3100

Krever opptak til studieprogram: Psykologi (MPSY) - studieretning i Psykologisk vitenskap og Teknologi