Master of Science in Stochastics and Data Science
University of Turin
EUR 2,800 / per year **
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* APPLY at UniTo for a.y. 2020-2021 at https://apply.unito.it
** per year
APPLY at UniTo for a.y. 2020-2021 at https://apply.unito.it
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The MSc in Stochastics and Data Science is a two-year graduate course that aims at preparing students with modern education in probabilistic, statistical and computational methods.
Inspired by the best programmes in Data Science recently started in the USA and Europe, this course brings together the expertise of three Departments of the University of Torino and their research groups in Probability, Statistics and Computer Science, and is currently the only offer of this type in Italy to award a degree in Mathematics.
The Programme is entirely taught in English and will provide students with a solid knowledge of key topics in Applied Mathematics, Probability, Statistics and Machine Learning. These are nowadays essential tools for performing mathematical modelling under uncertainty and for analyzing complex, high dimensional datasets with a deep mathematical understanding of the underneath structures.
The Programme in pills
- Regular duration: 2 years
- Formal validity of the degree: Laurea Magistrale in the class LM-40 Mathematics within the Italian University system
- Emphasis: probabilistic, statistical and computational methods
- Teaching language: English
What are "Stochastics" and "Data Science"?
The Master's Degree in Stochastics and Data Science aims at preparing students with a solid and modern education in probabilistic and statistical methods. Core topics will be advanced methodologies and techniques that are nowadays required tools for performing mathematical modeling and analysis under uncertainty (Stochastics) and for analyzing and being able to interpret high-dimensional and complex data structures (Data Science). The emphasis of the course topics will be both theoretical and oriented towards computation and applications, providing not a "book of recipes" but the capability of discerning, combining and applying the most useful and modern methods available in Probability and Statistics.
The Master's Degree in Stochastics and Data Science draws inspiration from the best graduate programmes in Data Science recently started in the USA and Europe, and is currently the only offer of this type in Italy.
Why should I be willing to obtain a degree in Stochastics and Data Science?
We live in an era with the huge availability of information. Think for example about the amount of data the social networks generate, where every click is registered and archived for future use. Being able to model and interpret this information is crucial, whatever the scope.
It then comes to no surprise, that one of the leading job figures of the 21st century is going to be that of data scientist. In the past few years, jobs analysts have constantly been ranking Mathematicians, Statisticians and Data Scientists among the best and most requested jobs, with even better future scenarios.
What can I do after completing this Master's Degree?
Gaining solid skills related to the above-outlined topics will enable us to deal with and model data collected in a variety of disciplinary fields by exploiting a deep mathematical understanding of the underneath structures. Graduates in Stochastics and Data Science will have a solid knowledge of key topics from Applied Mathematics, Probability and Statistics combined with computational skills essential for modern interdisciplinary applications. Such preparation allows to use this theoretical knowledge for concrete tasks, for example:
- autonomously formulating complex probabilistic models for describing static and dynamic phenomena of interest;
- developing the necessary mathematical and statistical tools for their analysis;
- using these models together with sets of available data to perform estimation, forecasting and uncertainty quantification of phenomena under study;
- designing and implementing computational strategies in the form of algorithms for concretely carrying out the statistical procedures.
Such skills are nowadays highly demanded in a variety of professional environments, both in the private and in the public sector.
Alternatively, those more interested in proceeding with Ph.D. studies will have gained a solid background which allows entering programmes in Statistics, Mathematics, Applied Mathematics, Operations Research, Computer Science, Economics and Mathematical Finance, among other topics.
What degree does this Programme award?
The Master's degree in Stochastics and Data Science is a second-cycle degree legally recognised as a Laurea Magistrale in the class LM-40 Mathematics within the Italian university system.
Who is the Master's Degree aimed at?
The Master's Degree in Stochastics and Data Science is aimed at highly motivated students who have obtained or are close to obtaining a Bachelor Degree (Laurea Triennale for students in Italian Universities) or an equivalent title. A Bachelor education in Mathematics, Statistics, Physics or Computer Science is ideal, but talented and motivated students with a different degree and willing to enroll in a challenging and exciting course are also welcome to apply for admission.
Students who need to consolidate their mathematical background will be given suggestions for self-organised study at the admission and during the first semester. To the same end, these are also encouraged to choose their free credits for the Bachelor Degree (Laurea Triennale) on courses in quantitative methods, most notably analysis, probability, statistics, operations research and econometrics.
Graduates in Stochastics and Data Science can work in private and public companies, research institutions or as self-employed. Among the possible career opportunities, there are analytic departments of banks and insurance companies, industries of all sectors, public administrations and research centers in all fields that require skilled treatment of data with complex structures.
Graduates in Stochastics and Data Science can also access PhD programmes in statistics, probability, applied mathematics, operations research and mathematical finance, among others.