Later stage Data Science: Master programme

The Data Science Programme provides students with an intensive and broad education in data collection, data processing, information analysis, information modelling and decision-making, which are components in the so-called Business Intelligence chain (BI). The programme integrates the most important components from Artificial Intelligence, data analysis of business data, and information systems with statistical principles. The design aims both to develop the ability of students to meet increasing global challenges in their careers and to give capacity to work within such diverse areas as data analysis research to enterprise management. In year one, students broaden their knowledge and skills in the main field of study, Microdata Analysis. A number of courses at the start of the programme lay the foundation for the rest of the programme. Courses in the first year focus on the analysis of business data using statistical and computer science methods in a BI context. Additionally, questions relating to data collection and data quality are discussed. By the end of the first year, the foundation for how to utilise various technologies will have been laid. The first year of the programme is when students gain practical skills in collecting, storing and analysing data. In year two, students are taught about and tested on issues that are relevant to data modelling and data analysis. Second-year courses aim to deepen and broaden the knowledge that students acquire in the first year. For example, students gain a deeper knowledge of data modelling and also learn how to analyse spatial data. In the second year, students formulate a basic outline for their thesis work. In the plan, a problem is identified and a research outcome is formulated. The plan must describe how the problem will be solved and what material the work will be based on, as well as how access to this can be assured. In addition, the plan outlines what the student needs to learn to be able to complete the thesis, and on the basis of these needs, appropriate elective courses are chosen. The plan is presented to a supervisory group. In the final semester, students complete their thesis work. The thesis work can be methodological in nature and contribute to the development of methods and techniques within the field of microdata analysis. It can also be practical in nature and aim to strengthen the BI chain of an organisation or improve it in some form.