Statistical Data Analytics, Computing Sciences and Electrical Engineering
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 Statistical Data Analytics (MSc) specialisation features several similar topic areas as the Data Science (MSc) specialisation but the Statistical Data Analytics (MSc) specialisation places more emphasis on aspects of data science and artificial intelligence where statistical understanding and modeling of data uncertainty, variation and dependency is a crucial advantage.
Statistical Data Analytics (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.
Statistical Data Analytics (MSc) is one of the specialisations in the Master’s Programme in Computing Sciences and Electrical Engineering.
Detailed information on the content and structure of the studies is included in the curriculum.
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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