Computing Science – Data Science
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: 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 Machine Learning (M.Sc. Tech) track focuses on engineering accurate predictive machine learning models.
Data Science (M.Sc.) track features several similar topic areas as Statistical Data Analytics track, but Data Science (M.Sc.) track places more emphasis on algorithmic and computational aspects of data science.
Data Science (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.
Data Science (M.Sc.) track is one of the seven tracks in the Master’s degree program in Computing Sciences.
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To be eligible to apply to a Master’s degree program at Tampere University, you must have
- 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 program that you’re applying to
- from an accredited institution of higher education
- AND a good command of the English language for academic purposes.
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.
Program-specific eligibility criteria
To be eligible to apply to the Master's degree program in Computing Sciences, Data Science (M.Sc.) track, you must have a successfully completed Bachelor’s degree or equivalent in
- Computer Science, Statistics or Mathematics or in another applicable field.
For more information about admission requirements, please visit the university website.
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General Studies in the Master's Degree program in Computing Sciences M.Sc.
General studies for international student
- Personal Study Planning
- Finnish Elementary Course 1
- Scientific Writing
General studies for students with school education in Finnish and Bachelor's degree taken outside Tampere University
- Swedish Written and Oral Skills
- Personal Study Planning
- Scientific Writing
General studies for students who have taken their Bachelor's degree in Finnish at Tampere University
- Personal Study Planning
Advanced Studies in Data Science
Compulsory Joint Studies
- Master's Thesis, Computational and Statistical Data Analytics
- Maturity Test in Finnish in Master’s Degree, content and language
- Maturity Test in Swedish in Master’s Degree, content and language
- Maturity Test in English in Master’s Degree, content and language
- Master's Thesis Seminar, Data Science & Statistical Data Analytics
Studies in Computational Data Analytics
- Data Structures and Algorithms 2
- Data Mining
- Machine Learning Algorithms
- Recommender Systems
- Big Data Entity Resolution
- Pattern Recognition and Machine Learning
- Knowledge Mining and Big Data
- Data-Intensive programing
Studies in Statistical Data Analytics
- Introduction to Bayesian Analysis 1
- Statistical Modeling 1
- Statistical Inference 2
- Introduction to Bayesian Analysis 2
- Learning from Multiple Sources
- Dimensionality Reduction and Visualization
- Time Series Analysis
- Advanced Regression Methods
- Spatial Data Analysis
- Statistical Methods for Text Data Analysis
- Functional and Shape Data Analysis
- Financial Mathematics and Statistics
- Complex Networks
- Bayesian filtering and smoothing
- Statistical Modeling 2
- Statistical Analysis with Missing Data
- Longitudinal and Finite Nonlinear Mixture Modelling and Associated Experimental Design Strategies
Free choice studies
Free Choice Study Modules
- Free Choice Course Units in Statistical Data Analytics
- Practical Training in Statistics
- Developing Intercultural Competence
- International Student Tutoring
- Finnish Society and Culture
- Introduction to Statistical Methods
- Statistical inference 1
- Data Structures and Algorithms 1
- Introduction to Statistics
- Introduction to Probability and Statistical Inference
- Programming 1: Introduction to programming
- Programming 2: Structures
Scholarships & funding
Several scholarship options are available. Please visit the university website for more information.
Tuition fee for non-EU/EEA citizens: 12000 € per academic year.
You will not be required to pay the fee if you are:
- an EU/EEA citizen
- equivalent to EU/EEA citizen (i.e. citizen of Switzerland)
- already reside in Finland (a continuous A or a permanent P/P-EU residence permit), or have an EU Blue Card issued in Finland. The exempting residence permit must be valid when you are applying for studies and at least until 1 August i.e. when the study right commences. Please note that a residence permit in another EU/EEA country does not exempt you from the tuition fee.
Upon successful completion of the program, students will earn a Master of Science degree (120 ECTS).
Students having completed the Master’s Degree program in Computing Sciences will
- have a thorough command of their own Computing Sciences specialisation and be capable of working as experts and developers in the field of their own specialisation
- be familiar with scientific thinking and capable of applying scientific working methods in their own area of specialisation in relevant tasks
- be capable of applying the acquired knowledge and skills in international working life
- possess prerequisites for scientific doctoral (postgraduate) training
- have sufficient communication and co-operation skills required for work, scientific activities and public social discussion concerning their field of expertise
- be conversant with the ethical norms of their own field of expertise and apply these in their own work and research
- have prerequisites for continuous professional development and are motivated for lifelong learning.
Postgraduate study opportunities
This master's degree provides the required background if you wish to pursue doctoral studies, for example in Doctoral program in Information and Systems at Tampere University.
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.
About this institute
Tampere University is one of the most multidisciplinary universities in Finland. Almost all internationally recognised fields of study are represented at our university. Tampere University is a merger of the former University of Tampere and Tampere University of Technology. University...
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