Data is the driving force behind today's information-based society. There is a rapidly increasing demand for specialists who are able to exploit the new wealth of information in large and complex systems.
The programme focuses on modern methods from machine learning and database management that use the power of statistics to build efficient models, make reliable predictions and optimal decisions. The programme provides students with unique skills that are among the most valued on the labour market.
The rapid development of information technologies has led to the overwhelming of society with enormous volumes of information generated by large or complex systems. Applications in IT, telecommunications, business, robotics, economics, medicine, and many other fields generate information volumes that challenge professional analysts. Models and algorithms from machine learning, data mining, statistical visualisation, computational statistics and other computer-intensive statistical methods included in the programme are designed to learn from these complex information volumes. These tools are often used to increase the efficiency and productivity of large and complex systems and also to make them smarter and more autonomous. This naturally makes these tools increasingly popular with both governmental agencies and the private sector.
The programme is designed for students who have basic knowledge of mathematics, applied mathematics, statistics and computer science and have a bachelor’s degree in one of these areas, or an engineering degree.
Most of the courses included in the programme provide students with deep theoretical knowledge and practical experience from massive amounts of laboratory work.
Students will be given the opportunity to learn:
The programme contains a wide variety of courses that students may choose from. Students willing to complement their studies with courses given at other universities have the possibility to participate in exchange studies during the third term. Our partner programmes were carefully selected in order to cover various methodological perspectives and applied areas.
During the final term of the programme, students receive help in finding a private company or a government institution where they can work towards their thesis. There they can apply their knowledge to a real problem and meet people who use advanced data analytics in practice.
With a Master's degree in Applied Statistics you will have the knowledge and the qualifications to assume a leading role in the design of statistical surveys and to contribute to the development of statistical analysis. Potential employers are banks and insurance companies, market research firms, as well as the industry sector, especially the pharmaceutical industry.
The Master's programme prepares students for careers as statisticians in both the private and the public sectors. Statistical methods are used all over the world and students of the Master's programme gain access to the international job market.
The programme gives students training for the profession of statistician. The programme also prepares students for studies at the doctoral level. The training covers many areas of statistical theory giving opportunities to work in different fields of application of statistical methodology, although a focus of the programme is on applications within the economic and social sciences. The Master in Applied Statistics gives deep and wide theoretical knowledge with a focus on practical application of theory and methodology. Statisticians usually work closely with colleagues who have training in other subjects than statistics, in particular experts on the actual area of application. Here the statistician is considered as a special resource for implementation of surveys and statistical analysis. The ability to communicate with non-statisticians is therefore important. This is due in part to the need to identify the information requirements and the restrictions surrounding the statistical study, but also in order to communicate the design chosen for the study and the results obtained. Communication with non-statisticians is practised throughout the programme.
The programme is made up of four semesters. The programme starts with a course in mathematics and a course in statistical theory. During the first year, students will also take two courses in econometrics, two courses on the theories and methods in the area of survey methodology and courses in computational statistics and Bayesian statistics. The third and the fourth semesters each includes two courses and one 15 credit Master's thesis. The student writes two Master's theses on the programme, one during the third semester and one during the fourth semester. After completion of the programme, the student has the training needed to take a leading role in the design and implementation of statistical surveys and analyses, as well as the ability to contribute to the development of statistical methodology.