Understanding data about human behaviour is an important and valuable skill in today's society. Companies, public institutions and governmental organizations — they all use the continuous stream of big data to describe and predict human behaviour.
Behavioural Data Science
The police use data to predict the risk of burglary by area and week of the year, insurance companies adjust their prices based on client data, and schools adjust educational programmes based on what is known about student progress.
Leveraging the full potential of these massive amounts of behavioural data towards these goals greatly benefits from a thorough understanding of data science techniques and human behaviour modelling. The master's track Behavioural Data Science aims to combine these two. The programme assumes knowledge of psychology, research methodology, and applied statistics at an undergraduate level, and continues with training on advanced (big) data techniques, academic skills, as well as practical and professional skills.
The goal of the programme is to equip students with in-depth knowledge of relevant big data and statistical learning techniques, psychological measurement, and a broad set of practical skills so that they can successfully start a career in data science. The programme contains four mandatory courses (18 EC), one to two elective courses (6 EC), two internships (3 + 15 EC), and a thesis (18 EC).
The four mandatory courses are Introduction to Behavioural Data Science, Big Data Analytics, Data Visualisation, and Psychometrics.
The course Introduction to Behavioural Data Science gives an overview of different kinds of data science projects and focuses on several skills that are necessary for effectively solving a client’s problem. It includes extensive interview training, some data wrangling programming skills, and an introduction to visualising statistical results. The course Big Data Analytics focuses on the most popular statistical and machine learning techniques necessary for extracting insights from large amounts of data. These techniques are discussed within the context of statistical methods taught in bachelor courses and are applied to a wide range of applications using multiple software tools (R, Excel, SQL). The course Data Visualisation encompasses the principles of data visualisation, and a training of some state-of-the-art visualisation tools (e.g. Tableau, ggplot, Shiny). The course Psychometrics discusses methods to measure human behaviour and connects well-known psychometric techniques to the machine learning vocabulary. These techniques are applied to data obtained from different kinds of psychological and educational tests.
The programme contains 6 EC for one or two elective courses. These courses may be about statistical techniques, (e.g. Network Analysis, Structural Equation Modeling, or Multilevel Modeling), programming skills, or other topics of interest that are related to behavioural data science.
The need for trained data scientists is high. The career prospects are therefore very good. The track touches upon a wide range of topics and skills. Students have the opportunity to specialize in particular areas of behavioural data science.
Alumni from our department work as:
- data analysts
- data managers
- test developers
This school offers programs in:
Last updated October 11, 2018