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Make big sense of big data

Big data and data-driven methods are at the centre of modern computer science, statistics and computer engineering and hold great promise for the future.

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 study tracks that involve analysis, modeling, prediction, and computation with big data: the Data Science (M.Sc.) track and Statistical Data Analytics (M.Sc.) track focus on computational and statistical algorithms for data mining and machine learning, with differing emphases, and the Machine Learning (M.Sc. Tech) track focuses on engineering accurate predictive machine learning models.

Statistical Data Analytics (M.Sc.) track features several similar topic areas as the Data Science (M.Sc.) track but Statistical Data Analytics (M.Sc.) track places more emphasis on aspects of data science where statistical understanding and modeling of data variation and uncertainty is a crucial advantage.

Statistical Data Analytics (M.Sc.) 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 (M.Sc.) track is one of the seven tracks in the Master’s degree programme in Computing Sciences, a new degree programme starting in August 2020.

Study contents

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.

Analysis needs activities such as data cleansing, data integration, modeling and prediction, interactive and iterative visualisation of data, and models for the refinement of hypotheses and models. The presentation of intermediate and final results to decision-makers requires mastery of visualisation and reporting methods. Successful analysts need skills in both computational and statistical topics.

This track 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.

Career opportunities

As a graduate 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.

Eligibility criteria

Eligibility criteria in the Master’s degree programmes consist of two parts: Tampere University’s general eligibility criteria, and programme-specific eligibility criteria, which specify and/or add information to the general criteria. You must meet both to be considered eligible. Applicants who do not meet both the general eligibility and the programme-specific eligibility criteria will not be selected as students in Tampere University.

General eligibility

To be eligible to apply to a Master’s degree programme at Tampere University, you must have

  1. Bachelor’s degree – nationally recognized first cycle degree
    • which corresponds to at least 180 ECTS (European credits) or to three years of full-time study
    • from relevant field for the Master’s degree programme that you’re applying to
    • from an accredited institution of higher education
  2. AND a good command of the English language for academic purposes. For more information, please see Language requirements.

A Bachelor’s degree completed in a university outside Finland must provide eligibility for university-level master’s degree studies in the country in which it was awarded.

Applicants in their final final year of the Bachelor’s degree are eligible to apply if the degree will be completed by 31 July 2020. In this case, they may be accepted conditionally. Please see special instructions for applicants in the final year of the Bachelor’s degree.

Applicants with a Master’s degree may be admitted only for well-founded reasons and only if they are able to show that the new degree at Tampere University provides the applicant with significant new knowledge and skills.

Programme-specific eligibility criteria

To be eligible to apply to the Master’s degree programme in Computing Sciences, Statistical Data Analytics (M.Sc.) track, you must have a successfully completed Bachelor’s degree or equivalent in

  • Statistics, Computer Science, or Mathematics or in another applicable field.

The degree needs to include a sufficient amount of studies in statistics, and also a sufficient amount of studies in computer science and mathematics.

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