M.S. Computing Sciences, Data Science
The Computing Sciences – Data Science program from Tampere University teaches you to understand data analysis and master necessary skills, such as data cleansing, integration, modelling and prediction, and interactive exploration of data and models.
|Full-time Duration:||2 years|
|Starting in:||1st of August 2021|
|Tuition Fee:||€ 12,000/year|
|Location:||Central Campus, Tampere, Finland|
Experts on analyzing data are needed for solving challenging data driven problems such as understanding of text documents, conversation and social media; creating intelligent search engines; finding data-driven insights into phenomena of society, economy and culture; creating data-driven solutions for medical and biological problems; and enabling self-driving cars and autonomous robots.
- The analysis of data has a central role in the modern information society.
- Organisations 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 organisations – is useless unless it is analysed.
- Analysis is required to find regularities, such as trends or groupings, and to relate the data to other data sets within an organisation or in scattered online repositories.
“The student-teacher relationship in Finland is very free. You can talk to them and you are not scared of them. They are ready to listen, if you want to talk. They know your strengths and weaknesses and encourage you to concentrate on your strengths and develop your weaknesses.“
Bolarinwa // Nigeria // Master’s degree programme in Computational Big Data Analysis
As a graduate of the Computing Sciences – Data Science program from Tampere University you will have knowledge and skills for data analytics and understand the overall data analytics process. Such analysts can be employed in analysis firms, as in-house analysts in companies producing big data, and in companies and organisations that gather and analyse public and private data, including government agencies, journalism, insurance, law enforcement, and finance, as well as in public and private research.