The analysis of data has a central role in the modern information society. Organizations in both the public and private sector are collecting vast data sets, and an increasing amount of public sector data is made open. However, data - assumed to be an important asset for organizations - is useless unless it is analyzed. Analysis is needed to find regularities such as trends or groupings, and to relate the data to other data sets within an organization or in scattered online repositories.
The analysis needs activities such as data cleansing, data integration, modeling and prediction, interactive and iterative visualization of data and models for the refinement of hypotheses and models, and the presentation of intermediate and final results to the decision-makers using visualization and reporting methods. Successful analysts need skills in both computational and statistical topics.
This programme educates top-level experts in computational and statistical data analysis, who possess knowledge and skills for the aforementioned tasks and understand the overall processes of data analysis.
Such analysts can be employed, for example, in dedicated analysis firms, as in-house analysts in companies producing big data, and in numerous types of companies and organizations that gather and analyze public and private data, such as government, journalism, insurance, law enforcement, and finance, as well as in public and private research.
Learning Outcomes
Students will
-have a thorough command of their own specializations
-be familiar with scientific thinking and capable of applying scientific working methods in their own area of specialization
-be motivated for lifelong learning
-be capable of undertaking scientific postgraduate (doctoral) studies
-be capable of applying the knowledge acquired and of functioning in internationalizing working life
-be capable of communicating in scientific situations
-be conversant with the ethical norms of the field and apply these in their own work
Students having completed the Master’s degree in this programme will have the knowledge and skills to
-choose suitable data analysis methods for the analysis tasks at hand from a reasonably wide selection of methods, including methods that are necessary for integrating data from different data sources during data preprocessing and/or analysis
-apply these methods to analyze the data,
-use efficient computational and statistical methods to manage and analyze big data,
-visualize the data / analysis results.
Students also have the theoretical knowledge which allows them to
-apply the analysis methods in previously unknown situations,
-understand in which situations the methods may perform well.
Working Life Connections
This Master's degree programme is aiming at high competence in data analysis and data mining. The burgeoning demand for data analysts in several areas of companies and organisations of public sector makes employment opportunity very good. Both new small enterprises for data analysis are created and larger ones employ new experts in this field. Enterprises involved vary with a wide spectrum of areas from insurance and banking to media, education and technology. The demand from public sector directly generates new employees or indirectly creates vacancies in enterprises.
Internationalisation
Tampere University is committed to promoting justice and equality in society, to enhancing the well-being of citizens at home and abroad, and to advancing multiculturalism and sustainable development.
Programme studies foster multicultural contacts. Many teachers and students have an international background, and teaching groups combine both international and Finnish students. Language and Intercultural Communication courses are offered by the University Language Centre.
Degree students can apply to take exchange studies abroad and then transfer the credits taken to the University of Tampere (UTA) degree. Both UTA bilateral exchange agreements worldwide and Faculty-level exchange agreements especially in Europe can be utilised. UTA supports taking an internship abroad, and usually it is possible to get ECTS credits for an internship too. Programme students are also encouraged to act as student tutors to new arriving exchange and degree students.
Degree students can include an internationalisation module in their degree certificate if enough internationalising studies have been taken. For more on this please see http://www.uta.fi/studies/study_abroad/internationalization_module.html.