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Masters Degrees in Mathematics, Sweden

We have 7 Masters Degrees in Mathematics, Sweden

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Data is the driving force behind today's information-based society. There is a rapidly increasing demand for specialists who are able to exploit the new wealth of information in large and complex systems. Read more

Data is the driving force behind today's information-based society. There is a rapidly increasing demand for specialists who are able to exploit the new wealth of information in large and complex systems.

The programme focuses on modern methods from machine learning and database management that use the power of statistics to build efficient models, make reliable predictions and optimal decisions. The programme provides students with unique skills that are among the most valued on the labour market.

The rapid development of information technologies has led to the overwhelming of society with enormous volumes of information generated by large or complex systems. Applications in IT, telecommunications, business, robotics, economics, medicine, and many other fields generate information volumes that challenge professional analysts. Models and algorithms from machine learning, data mining, statistical visualisation, computational statistics and other computer-intensive statistical methods included in the programme are designed to learn from these complex information volumes. These tools are often used to increase the efficiency and productivity of large and complex systems and also to make them smarter and more autonomous. This naturally makes these tools increasingly popular with both governmental agencies and the private sector.

The programme is designed for students who have basic knowledge of mathematics, applied mathematics, statistics and computer science and have a bachelor’s degree in one of these areas, or an engineering degree.

Most of the courses included in the programme provide students with deep theoretical knowledge and practical experience from massive amounts of laboratory work.

Students will be given the opportunity to learn:

  • how to use classification methods to improve a mobile phone’s speech recognition software ability to distinguish vowels in a noisy environment
  • how to improve directed marketing by analysing shopping patterns in supermarkets’ scanner databases
  • how to build a spam filter
  • how to provide early warning of a financial crisis by analysing the frequency of crisis-related words in financial media and internet forums
  • how to estimate the effect that new traffic legislation will have on the number of deaths in road accidents
  • how to use a complex DNA microarray dataset to learn about the determinants of cancer
  • how interactive and dynamic graphics can be used to determine the origin of an olive oil sample.

The programme contains a wide variety of courses that students may choose from. Students willing to complement their studies with courses given at other universities have the possibility to participate in exchange studies during the third term. Our partner programmes were carefully selected in order to cover various methodological perspectives and applied areas.

During the final term of the programme, students receive help in finding a private company or a government institution where they can work towards their thesis. There they can apply their knowledge to a real problem and meet people who use advanced data analytics in practice.



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With a Master's degree in Applied Statistics you will have the knowledge and the qualifications to assume a leading role in the design of statistical surveys and to contribute to the development of statistical analysis. Read more

With a Master's degree in Applied Statistics you will have the knowledge and the qualifications to assume a leading role in the design of statistical surveys and to contribute to the development of statistical analysis. Potential employers are banks and insurance companies, market research firms, as well as the industry sector, especially the pharmaceutical industry.

The Master's programme prepares students for careers as statisticians in both the private and the public sectors. Statistical methods are used all over the world and students of the Master's programme gain access to the international job market.

The programme gives students training for the profession of statistician. The programme also prepares students for studies at the doctoral level. The training covers many areas of statistical theory giving opportunities to work in different fields of application of statistical methodology, although a focus of the programme is on applications within the economic and social sciences. The Master in Applied Statistics gives deep and wide theoretical knowledge with a focus on practical application of theory and methodology. Statisticians usually work closely with colleagues who have training in other subjects than statistics, in particular experts on the actual area of application. Here the statistician is considered as a special resource for implementation of surveys and statistical analysis. The ability to communicate with non-statisticians is therefore important. This is due in part to the need to identify the information requirements and the restrictions surrounding the statistical study, but also in order to communicate the design chosen for the study and the results obtained. Communication with non-statisticians is practised throughout the programme.

The programme is made up of four semesters. The programme starts with a course in mathematics and a course in statistical theory. During the first year, students will also take two courses in econometrics, two courses on the theories and methods in the area of survey methodology and courses in computational statistics and Bayesian statistics. The third and the fourth semesters each includes two courses and one 15 credit Master's thesis. The student writes two Master's theses on the programme, one during the third semester and one during the fourth semester. After completion of the programme, the student has the training needed to take a leading role in the design and implementation of statistical surveys and analyses, as well as the ability to contribute to the development of statistical methodology.



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Why study Data Science?. Data abounds. Social media, manufacturing systems, medical devices, logistic services, and countless others generate petabytes of data on a daily basis. Read more

Why study Data Science?

Data abounds. Social media, manufacturing systems, medical devices, logistic services, and countless others generate petabytes of data on a daily basis. With a wealth of data available, we are at a point in history, where we can conduct analyses to detect, discover, and, ultimately, better understand the world around us.

What are the career opportunities?

Data science is a highly innovative area. The profession was described as "Sexiest Job of the 21st Century," by Harvard Business Review in October 2012. The data scientist simultaneously masters scalable data management, data analysis and domain area expertise to extract key knowledge and solve real-world problems. Data scientists’ skills are highly valued across all fields within the private sector, government and non-profit organisations. This is an opportune time to pursue training in both a challenging and rewarding area of expertise. So join us and embark on a journey of a lifetime!

Why choose Data Science at EIT Digital?

The Data Science Masters offers a unique two-year academic programme, whereby students study data science, innovation and entrepreneurship at two different leading European universities.

Students acquire in-depth technical skills in scalable data collection techniques and data analysis methods. They learn how to use and develop a suite of tools and technologies that address data capture, processing, storage, transfer, analysis, visualisation, and related concepts (e.g., data access, data pricing, and data privacy).

At the same time, they also acquire extensive business skills by learning how to bring an innovation to the market and developing a successful business model. These additional entrepreneurial skills will give students their ticket to a successful career.

How is the programme structured?

All EIT Digital Master School programmes follow the same scheme:

  • Students study one year at an ‘entry’ university and one year at an ‘exit’ university in two of EIT Digital’s hot spots around Europe.
  • Upon completion, graduates receive degrees from the two universities and a certificate awarded by the European Institute of Innovation and Technology.
  • The first year is similar at all entry points with basic courses to lay the foundation for the chosen technical programme focus. Some elective courses may also be chosen. At the same time, students are introduced to business and management. During the second semester, a design project is combined with business development exercises. These teach how to turn technology into business and how to present a convincing business plan.
  • In between the first year and the second year, a summer school addresses business opportunities within a socially relevant theme.
  • The second year offers a specialisation and a graduation project. The gradation project includes an internship at a company or a research institute and results in a Master thesis with a strong innovation and entrepreneurship dimension.

To learn more about the structure of the programme, please click here.

To learn more about the Innovation & Entrepreneurship minor, please click here.

Where can I study Data Science?

Entry - 1st year, common courses

  • Eindhoven University of Technology (TU/e), The Netherlands
  • Royal Institute of Technology (KTH)
  • Universidad Politecnica de Madrid (UPM), Spain
  • Universite Nice Sophia Antipolis (UNS), France
  • Politecnico di Milano (POLIMI), Italy

Exit - 2nd year, specialisation

  • Infrastructures for Large Scale Data Management and Analysis at Universidad Politecnica de Madrid (UMP), Spain
  • Multimedia and Web Science for Big Data at Université de Nice Sophia Antipolis (UNS), France
  • Business Process Intelligence at Eindhoven University of Technology (TU/e), The Netherlands
  • Distributed Systems and Data Mining for Big Data at The Royal Institute of Technology (KTH), Sweden
  • Design, Implementation, and Usage of Data Science Instruments at Technische Universität Berlin (TUB), Germany
  • Machine Learning, Big Data Management, and Business Analytics at Aalto University, Finland
  • Real-time Data Analytics at Eötvös Lorand University (ELTE), Hungary

About EIT Digital Master School

EIT Digital Master School offers two-year, European Masters in computer science and information technology, with a focus on innovation and entrepreneurship. Students study two years in two leading European universities. They earn two Masters degrees from those universities together with a certificate awarded by the European Institute of Innovation and Technology (EIT). Students enjoy an array of benefits which includes European mobility, a three-day business challenge, a two-week Summer School, an internship and access to the EIT Digital community. Upon graduation, students are equipped with the tools to become digital innovators.

Scholarship:

·        European citizen: No tuition fees. Up to 750 Euros monthly allowance

·        Non-European citizen: tuition fee waiver of up to 50% and 750 Euros monthly allowance

Application deadline to begin studying in September 2018:

·        15 April 2018 (Open to EU/EEA/CH citizens/ Non-EU citizens*.)

*Please note that this application period is not recommended for applicants who require a visa due to time constraints. If you require a visa to study in an EU country, we recommend you delay your application to November 2018 when the application portal opens again, to start in Autumn 2019.

How should you apply?

To apply, you need to register and submit your application on the EIT Digital Application Portal. You don’t need to do your application all at once. You can access the list of required documents for your application here.

Need more information?

Master School Office: , we will be happy to help.



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