Data Science, Computing Sciences
Make big sense of big data
Extent of studies
Tuition fee for non-EU/EEA citizens
Link to scholarship programme
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.
Tampere University offers three related specialisations that involve analysis, modeling, prediction, and computation with big data: the Data Science (MSc) specialisation and the Statistical Data Analytics (MSc) specialisation focus on computational and statistical algorithms for data mining and machine learning, with differing emphases, and the Signal Processing and Machine Learning (MSc Tech) specialisation focuses on engineering accurate predictive machine learning models.
The Data Science (MSc) specialisation features several similar topic areas as the Statistical Data Analytics specialisation , but the Data Science (MSc) specialisation places more emphasis on algorithmic and computational aspects of data science and artificial intelligence.
Data Science (MSc) 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. You will learn methods ranging from probabilistic approaches through efficient data mining algorithms to flexible deep learning with neural networks. You will also learn to present data analysis results to decision-makers with descriptive summaries and visualisations.
The Data Science (MSc) specialisation is one of the seven specialisations in the Master’s Programme in Computing Sciences, a programme that started in August 2020.
Become a student
Learn more about the studies, admissions, and eligibility criteria on Studyinfo. In addition, applications are submitted via the Studyinfo.fi service.
For more information
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